Europe has experienced a substantial increase in non-indigenous crayfish species (NICS) since the mid-20th century due to their extensive use in fisheries, aquaculture and, more recently, pet trade. Despite relatively long invasion histories of some NICS and negative impacts on biodiversity and ecosystemfunctioning, large spatio-temporal analyses of their occurrences are lacking. Here, we used a large freshwater macroinvertebrate database to evaluate what information on NICS can be obtained from widely applied biomonitoring approaches and how usable such data is for descriptions of trends in identified NICS species. We found 160 time-series containing NICS between 1983 and 2019, to infer temporal patterns and environmental drivers of species and region-specific trends. Using a combination of metaregression and generalized linear models, we found no significant temporal trend for the abundance of any species (Procambarus clarkii, Pacifastacus leniusculus or Faxonius limosus) at the European scale, but identified species-specific predictors of abundances. While analysis of the spatial range expansion of NICS was positive (i.e. increasing spread) in England and negative (significant retreat) in northern Spain, no trend was detected in Hungary and the Dutch- German-Luxembourg region. The average invasion velocity varied among countries, ranging from 30 km/year in England to 90 km/year in Hungary. The average invasion velocity gradually decreased over time in the long term, with declines being fastest in the Dutch-German-Luxembourg region, and much slower in England. Considering that NICS pose a substantial threat to aquatic biodiversity across Europe, our study highlights the utility and importance of collecting high resolution (i.e. annual) biomonitoring data using a sampling protocol that is able to estimate crayfish abundance, enabling a more profound understanding of NICS impacts on biodiversity.
As the number of introduced species keeps increasing unabatedly, identifying and prioritising current and potential Invasive Alien Species (IAS) has become essential to manage them. Horizon Scanning (HS), defined as an exploration of potential threats, is considered a fundamental component of IAS management. By combining scientific knowledge on taxa with expert opinion, we identified the most relevant aquatic IAS in the Iberian Peninsula, i.e., those with the greatest geographic extent (or probability of introduction), severe ecological, economic and human health impacts, greatest difficulty and acceptability of management. We highlighted the 126 most relevant IAS already present in Iberian inland waters (i.e., Concern list) and 89 with a high probability of being introduced in the near future (i.e., Alert list), of which 24 and 10 IAS, respectively, were considered as a management priority after receiving the highest scores in the expert assessment (i.e., top-ranked IAS). In both lists, aquatic IAS belonging to the four thematic groups (plants, freshwater invertebrates, estuarine invertebrates, and vertebrates) were identified as having been introduced through various pathways from different regions of the world and classified according to their main functional feeding groups. Also, the latest update of the list of IAS of Union concern pursuant to Regulation (EU) No 1143/2014 includes only 12 top-ranked IAS identified for the Iberian Peninsula, while the national lists incorporate the vast majority of them. This fact underlines the great importance of taxa prioritisation exercises at biogeographical scales as a step prior to risk analyses and their inclusion in national lists. This HS provides a robust assessment and a cost-effective strategy for decisionmakers and stakeholders to prioritise the use of limited resources for IAS prevention and management. Although applied at a transnational level in a European biodiversity hotspot, this approach is designed for potential application at any geographical or administrative scale, including the continental one.
Seagrass systems are in decline, mainly due to anthropogenic pressures and ongoing climate change. Implementing seagrass protection and restoration measures requires accurate assessment of suitable habitats. Commonly, such assessments have been performed using single-algorithm habitat suitability models, nearly always based on low environmental resolution information and short-term species data series. Here we address eelgrass (Zoostera marina) meadows’ large-scale decline (>80%) in Shandong province (Yellow Sea, China) by developing an ensemble habitat model (EHM) to inform eelgrass conservation and restoration strategies in the Swan Lake (SL). For this, we applied a weighted EHM derived from ten single-algorithm models including profile, regression, classification, and machine learning methods to generate a high-resolution habitat suitability map. The EHM was constructed based on the predictive performances of each model, by combining a series of present-absent eelgrass datasets from recent years coupled with oceanographic and sediment data. The model was cross-validated with independent historical datasets, and a final habitat suitability map for conservation and restoration was generated. Our EHM scheme outperformed all single models in terms of habitat suitability, scoring ∼0.95 for both true statistic skill (TSS) and area under the curve (AUC) performance criteria. Machine learning methods outperformed profile, regression and classification methods. Regarding model explanatory variables, overall, topographic characteristics such as depth (DEP) and seafloor slope (SSL) are the most significant factors determining the distribution of eelgrass. The EHM predicted that the overlapping area was almost 90% of the current eelgrass habitat. Using results from our EHM, a LOESS regression model for the relationship of the habitat suitability to both the biomass and density of Z. marina outperformed better than the classic Ordinary Least Squares regression model. The EHM is a promising tool for supporting eelgrass protection and restoration areas in temperate lagoons as data availability improves.
The IEC 61000–2–2 standard defines the compatibility levels to evaluate the conducted disturbances in the low voltage grid for the 2-150 kHz range. For frequencies 9–150 kHz, they are defined in terms of quasi peak values measured according to CISPR 16–1–1 standard, but no clear guidance is given on how to apply this standard to grid measurements. The definition of the method in CISPR 16–1–1 accepts a wide range of different implementations, all of them fulfilling the compliance requirements. The reasons are that the standard does not propose a fixed implementation but a ‘black-box’ approach, and some of the proposed configuration values are non-normative and/or wide tolerances are allowed. In this context, some parameters have a pivotal role in the results provided by the method. The impact of variation of these parameters on the measurement results is addressed in this work. In particular, the accuracy requirements and the reproducibility issues of the standard are studied. For that purpose, a high number of different compliant implementations have been developed and the influence of different features of the CISPR 16–1–1 method on the results of these implementations is identified and analyzed. The results show that the wide tolerances allowed by the CISPR 16 specification impede the comparison of results provided by measuring receivers based on different implementations of the standard. Results of the study also show that reproducibility issues for the same input signal may be relevant and generate inconsistences. Moreover, a fixed specific configuration does not ensure that uncertainty issues are solved, as the technical approach used in the implementation of the damped meter has a strong influence on the outputs. An unambiguous guidance of digital implementation of the standard could fix these issues.
Process digitalisation and automation is unstoppable in all industries, including construction. However, its widespread adoption, even for non-experts, demands easy-to-use tools that reduce technical requirements. BIM to BEM (Building Energy Models) workflows are a clear example, where ad-hoc prepared models are needed. This paper describes a methodology, based on graph techniques, to automate it by highly reducing the input BIM requirements found in similar approaches, being applicable to almost any IFC. This is especially relevant in retrofitting, where reality capture tools (e.g., 3D laser scanning, object recognition in drawings) are prone to create geometry clashes and other inconsistencies, posing higher challenges for automation. Another innovation presented is its multi-scale nature, efficiently addressing the surroundings impact in the energy model. The application to selected test cases has been successful and further tests are ongoing, considering a higher variety of BIM models in relation to tools and techniques used and model sizes.
Among biomedical community, great efforts have been realized to develop antibacterial coatings that avoid implant-associated infections. To date, conventional mono-functional antibacterial strategies have not been effective enough for successful long-term implantations. Consequently, researchers have recently focused their attention on novel bifunctional or multifunctional antibacterial coatings, in which two or more antibacterial mechanisms interact synergistically. Thus, in this work different chitosan-based (CHI) hydrogel coatings were created on Ti6Al4V surface using genipin (Ti-CHIGP) and polyethylene glycol (Ti-CHIPEG) crosslinking agents. Hydrogel coatings demonstrated an exceptional in vivo biocompatibility plus a remarkable ability to promote cell proliferation and differentiation. Lastly, hydrogel coatings demonstrated an outstanding bacteria-repelling (17-28 % of S. aureus and 33-43 % of E. coli repelled) and contact killing (186-222 % of S. aureus and 72-83 % of E. coli damaged) ability. Such bifunctional antibacterial activity could be further improved by the controlled release of drugs resulting in powerful multifunctional antibacterial coatings.
A six lump-based kinetic model has been developed for the hydrocracking of high-density polyethylene (HDPE) blended with vacuum gas oil (VGO) over a PtPd/HY zeolite catalyst. The blend (20 wt% HDPE and 80 wt% VGO) has been hydrocracked in a semi-continuous stirred tank reactor under the following conditions: 400–440 °C; 80 H2 bar; catalyst to feed (C/F) weight ratio, 0.05–0.1 gcat gfeed⁻¹; reaction time, 15–120 min; and stirring rate, 1300 rpm. The kinetic model, which is an approach to tackle the complex reaction mechanism behind the hydrocracking of a HDPE/VGO blend, predicts the evolution over time of product distribution (gas, naphtha, light cycle oil (LCO), heavy cycle oil (HCO), HDPE and coke). The kinetic model and its computed parameters have been used for the simulation of the HDPE/VGO hydrocracking establishing that a C/F ratio of 0.075 gcat gfeed⁻¹ and temperature–time combinations of 430 °C–10 min and 440 °C–70 min are the optimal operating conditions. Under these conditions, a proper balance between the HCO conversion (>80 %), HDPE conversion (>60 %) and liquid fuel production index (>1.0) would be obtained. This kinetic model could serve as a basis for scaling-up in the valorization of waste plastics by co-feeding them to industrial hydrocracking units, within a Waste-Refinery strategy.
There is growing interest in understanding the links between neighbourhood environmental attributes (i.e. greenness, walkability and air pollution) and human health. Recent research has analysed the mediating role of a diverse set of potential factors and studied the agreement between objective and perceived modalities of those attributes. In this study, we explored the connections between objective neighbourhood attributes, their perceived accounts and mental health during pregnancy, using a measure of social cohesion as potential mediator with data from two samples of pregnant women recruited during the 12th week of pregnancy in two Spanish cities (Donostialdea, n = 440; Barcelona n = 364). Besides, we ran analyses on the agreement between objective and perceived measures. We fitted four separate Structural Equation Models and detected associations between objective neighbourhood attributes and mental health occurred only through their perceived counterparts and the strengthening of social cohesion. We also found poor to fair agreement between greenness measures in both cities, walkability measures only in Donostialdea, and were unable to detect any meaningful agreement between air pollution variables. Using rescaled versions of neighbourhood attribute variables and in some instances, we saw that the higher the objective value of a given attribute, the larger the differences between objective and perceived accounts of such attributes.
Motivated by the necessity of intensifying the valorization of secondary refinery streams and of extending the life cycle of the catalysts, this study aims to obtain high quality gasoline in the hydrocracking of a pre-hydrotreated light cycle oil (HT-LCO) using noble metals catalysts supported on a spent fluid catalytic cracking (FCC) catalyst. Hydrocracking runs have been carried out in a fixed bed reactor with two different catalysts (Pt/FCC and Pd/FCC) under the following conditions: 320–400 °C; 80 bar; hydrogen to HT-LCO ratio, 1000 NmL mL⁻¹; weight hourly space velocity (WHSV), 4.48 h⁻¹; and time on stream (TOS), 8 h. The results have exposed that 400 °C is the optimal temperature for hydrocracking the HT-LCO, since the yield of gasoline is clearly maximized (yielding up to 80 wt%) at the same time that the formation of gases is minimized. Comparing both catalysts, the Pt/FCC catalyst has offered better performance as its high hydrogenation capacity has allowed for obtaining an isoparaffinic gasoline fraction with a RON of 93.0. These good results lay on two facts that avoid the blocking of the micropores of the zeolite HY by the deposition of coke: (i) the hydrocracking of the coke precursors; and (ii) the matrix of the FCC catalyst where a fraction of the coke is deposited. In this way, after an initial deactivation period, the catalysts have reached a pseudo-stable state with a notorious remaining catalytic activity (higher for the Pt/FCC catalyst).
Sensor integration is one of the drivers in modern industry for obtaining real-time data and enabling transition to Industry 4.0. Sensor integration on production systems and tooling is one of the key points for data acquisition. Although several techniques can be applied for sensor integration, Laser Directed Energy Deposition (L-DED) is becoming one of the most relevant, since the sensor can be placed into the manufactured layer-by-layer structure. However, the thermal nature of the L-DED poses a challenge when heat-sensitive parts, such as thermocouples, are to be embedded. In order to ease parametrization and anticipate the behavior of the L-DED process, modeling is an interesting tool that has attracted the attention of academia in the last years. Nevertheless, most models are highly complex and focused on a very local scale or include symmetry assumptions that restrict their use for real applications. In view of this need, in the present research work a thermal model that considers material addition and determines the clad geometry is developed. The model includes an automatic meshing algorithm that adapts the element size by refining the mesh where required. Besides, the model enables 5 axis L-DED, in-process variation of the machine feed rate, and allows to switch on and off the laser to simulate not only the material deposition, but also the idle movements. The model is validated in two steps: single clad deposition on a flat surface and single clads on a 0.3 mm thick thermocouple sheath. Finally, the validated model is used for defining the maximum laser power for embedding virtually a 3 mm diameter K-type thermocouple with a 0.3 mm thick sheath. The results of the simulation are also corroborated by experimental integration of the same thermocouple, which functionality is tested afterwards. Therefore, the L-DED modeling is proven to be an effective tool for manufacturing complex parts on the first try.
The global forest carbon (C) stock is estimated at 662 Gt of which 45% is in soil organic matter. Thus, comprehensive understanding of the effects of forest management practices on forest soil C stock and greenhouse gas (GHG) fluxes is needed for the development of effective forest-based climate change mitigation strategies. To improve this understanding, we synthesized peer-reviewed literature on forest management practices that can mitigate climate change by increasing soil C stocks and reducing GHG emissions. We further identified soil processes that affect soil GHG balance and discussed how models represent forest management effects on soil in GHG inventories and scenario analyses to address forest climate change mitigation potential. Forest management effects depend strongly on the specific practice and land type. Intensive timber harvesting with removal of harvest residues/stumps results in a reduction in soil C stock, while high stocking density and enhanced productivity by fertilization or dominance of coniferous species increase soil C stock. Nitrogen fertilization increases the soil C stock and N2O emissions while decreasing the CH4 sink. Peatland hydrology management is a major driver of the GHG emissions of the peatland forests, with lower water level corresponding to higher CO2 emissions. Furthermore, the global warming potential of all GHG emissions (CO2, CH4 and N2O) together can be ten-fold higher after clear-cutting than in peatlands with standing trees. The climate change mitigation potential of forest soils, as estimated by modelling approaches, accounts for stand biomass driven effects and climate factors that affect the decomposition rate. A future challenge is to account for the effects of soil preparation and other management that affects soil processes by changing soil temperature, soil moisture, soil nutrient balance, microbial community structure and processes, hydrology and soil oxygen concentration in the models. We recommend that soil monitoring and modelling focus on linking processes of soil C stabilization with the functioning of soil microbiota.
Transparent oxyfluoride glass-ceramic (OxGCs) coatings with composition 1.2Nd³⁺ 80SiO2- 20LaF3 were prepared following a sol-gel route labelled “pre-crystallized nanoparticles route”. OxGCs are transparent materials composed by one or more fluoride nanocrystals in a glass matrix. OxGCs have been prepared by sol-gel with encouraging results in powders and bulk glass-ceramics but not in coatings. In the present work, aqueous suspensions of LaF3 nanoparticles doped with Nd³⁺ were prepared by chemical route and then incorporated into a silica sol to obtain 1.2Nd³⁺ doped-80SiO2-20LaF3 particulate sols. Nd³⁺-LaF3 suspensions are characterized by XRD, HRTEM, and XRF revealing the presence of LaF3 as the unique crystalline phase. Then, 1.2Nd³⁺ -80SiO2-20LaF3 coatings were prepared by dip-coating and characterized by XRD, FTIR, and Ellipsometry. Photoluminescence measurements were performed for LaF3 nanoparticles and OxGCs coatings, confirming the presence of Nd³⁺ in the nanocrystals and showing well-structured crystalline-like emission spectra with lifetimes of 520 and 440 µs respectively.
Club-rush (Bolboschoenus spp. (Asch.) Palla) is one of the most common edible wild plant taxa found at Epipaleolithic and Neolithic sites in southwest Asia. At the Early Natufian site of Shubayqa 1 (Black Desert, Jordan) thousands of club-rush rhizome-tuber remains and hundreds of fragments of prepared meals were found. The evidence indicated that the underground storage organs of this plant were recurrently used as a source of food 14,600 years ago. To determine how Early Natufian communities gathered, processed and transformed club-rush tubers into food, we designed an interdisciplinary study that combined experimental archaeology, archaeobotany, and ground and chipped stone tool analyses. We conducted more than 50 specific experiments over three years, and based on the experimental materials produced we inferred that 1) the best season for club-rush rhizome-tuber collection in the region was spring-summer time; 2) that the primary method to harvest the plant would have been uprooting; and 3) that the most efficient approaches to obtain perfectly peeled and clean rhizome-tubers could have entailed drying, roasting and gentle grinding of the tubers. Overall, our work provides important information to reconstruct the chaîne opératoire for club-rush tuber exploitation in the past. The experimental data and modern reference datasets allow us to interpret the archaeological material found at Shubayqa 1, and start identifying some of the activities that Natufian communities in the Black Desert undertook in relation to the exploitation of this particular source of food.
Schizophrenia is frequently characterized by the presence of multiple relapses. Cognitive impairments are core features of schizophrenia. Cognitive reserve (CR) is the ability of the brain to compensate for damage caused by pathologies such as psychotic illness. As cognition is related to CR, the study of the relationship between relapse, cognition and CR may broaden our understanding of the course of the disease. We aimed to determine whether relapse was associated with cognitive impairment, controlling for the effects of CR. Ninety-nine patients with a remitted first episode of schizophrenia or schizophreniform disorder were administered a set of neuropsychological tests to assess premorbid IQ, attention, processing speed, working memory, verbal and visual memory, executive functions and social cognition. They were followed up for 3 years (n=53) or until they relapsed (n=46). Personal and familial CR was estimated from a principal component analysis of the premorbid information gathered. Linear mixed-effects models were applied to analyse the effect of time and relapse on cognitive function, with CR as covariate. Patients who relapsed and had higher personal CR showed less deterioration in attention, whereas those with higher CR (personal and familial CR) who did not relapse showed better performance in processing speed and visual memory. Taken together, CR seems to ameliorate the negative effects of relapse on attention performance and shows a positive effect on processing speed and visual memory in those patients who did not relapse. Our results add evidence for the protective effect of CR over the course of the illness.
The Ychsma society was one of the most important civilizations developed between 900 and 1532 CE in Lima, the present Peruvian capital, situated on the central coast of Peru. The Ychsma territory included the lower basin of the Rímac and Lurín valleys in the current city of Lima (Peru). Around 1470 CE, the Ychsma region was conquered and placed under the control of the Inca Empire, which ruled the region until the Spanish conquest in 1532 CE. Despite this, the Inca rule allowed local elites to maintain their position and control of the population. The archaeological site of Armatambo was an important administrative center of the Ychsma society. This site was actively occupied during the Middle Ychsma (1250–1350 CE) and Late Ychsma (1350–1532 CE) phases, and as the capital of the Sullco Curacazgo controlled a large part of the lower Rímac valley. During excavations at this site, many materials associated with ceramic production were found. One aspect crucial to the study of ceramic materials is the reconstruction of ceramic production and distribution networks, which allows us to obtain information linked to the social and economic interaction between communities. To determine the local or non-local origin of the materials found at Armatambo, 61 samples were analyzed using ICP-MS, Petrography, and SEM. The results were compared with archaeological and geological data from the Rímac valley to determine whether or not production there was local or non-local and to identify possible sources of raw materials.
Residual minimization is a widely used technique for solving Partial Differential Equations in variational form. It minimizes the dual norm of the residual, which naturally yields a saddle-point (min–max) problem over the so-called trial and test spaces. In the context of neural networks, we can address this min–max approach by employing one network to seek the trial minimum, while another network seeks the test maximizers. However, the resulting method is numerically unstable as we approach the trial solution. To overcome this, we reformulate the residual minimization as an equivalent minimization of a Ritz functional fed by optimal test functions computed from another Ritz functional minimization. We call the resulting scheme the Deep Double Ritz Method (D2RM), which combines two neural networks for approximating trial functions and optimal test functions along a nested double Ritz minimization strategy. Numerical results on different diffusion and convection problems support the robustness of our method, up to the approximation properties of the networks and the training capacity of the optimizers.
The Mars Environmental Dynamics Analyzer (MEDA) on board Perseverance includes first‐of‐its‐kind sensors measuring the incident and reflected solar flux, the downwelling atmospheric IR flux, and the upwelling IR flux emitted by the surface. We use these measurements for the first 350 sols of the Mars 2020 mission (Ls ∼ 6°–174° in Martian Year 36) to determine the surface radiative budget on Mars and to calculate the broadband albedo (0.3–3 μm) as a function of the illumination and viewing geometry. Together with MEDA measurements of ground temperature, we calculate the thermal inertia for homogeneous terrains without the need for numerical thermal models. We found that (a) the observed downwelling atmospheric IR flux is significantly lower than the model predictions. This is likely caused by the strong diurnal variation in aerosol opacity measured by MEDA, which is not accounted for by numerical models. (b) The albedo presents a marked non‐Lambertian behavior, with lowest values near noon and highest values corresponding to low phase angles (i.e., Sun behind the observer). (c) Thermal inertia values ranged between 180 (sand dune) and 605 (bedrock‐dominated material) SI units. (d) Averages of albedo and thermal inertia (spatial resolution of ∼3–4 m²) along Perseverance's traverse are in very good agreement with collocated retrievals of thermal inertia from Thermal Emission Imaging System (spatial resolution of 100 m per pixel) and of bolometric albedo in the 0.25–2.9 μm range from (spatial resolution of ∼300 km²). The results presented here are important to validate model predictions and provide ground‐truth to orbital measurements.
Objective: This work aims at evaluating longitudinally titers of antibodies against β2-glycoprotein I (β2GPI) and domain 1 (anti-D1), identifying predictors of the variation of anti-D1 and anti-β2GPI antibody titers and clarifying whether antibody titer fluctuations predict thrombosis in a large international cohort of patients persistently positive for antiphospholipid antibodies (aPL), the "APS ACTION Registry". Methods: Patients with available blood samples from at least 4 time points were included. Anti-β2GPI and anti-D1 IgG were tested by chemiluminescence (BioFlash, INOVA Diagnostics). Results: In a cohort of 230 patients, anti-D1 and anti-β2GPI titers decreased significantly over time (p<0.0001 and p=0.010, respectively). After adjustment for age, gender, and number of positive aPL tests, the fluctuation of anti-D1 and anti-β2GPI titers was associated with treatment with hydroxychloroquine (HCQ) at each time-point. Treatment with HCQ, but not immunosuppressors, was associated with 1.3-fold and 1.4-fold decrease in anti-D1 and anti-β2GPI titers, respectively. Incident vascular events were associated with 1.9-fold and 2.1-fold increase of anti-D1 and anti-β2GPI titers, respectively. Anti-D1 and anti-β2GPI titers at the time of thrombosis were lower compared to the other time-points: 1.6-fold decrease in anti-D1 titers and 2-fold decrease in anti-β2GPI titers conferred an OR for incident thrombosis of 6.0 (95%CI 0.62-59.3) and 9.4 (95%CI 1.1-80.2), respectively. Conclusions: Treatment with HCQ and incident vascular events significant predicted anti-D1 and anti-β2GPI titer fluctuation over time. Both anti-D1 and anti-β2GPI titers drop around the time of thrombosis, with potential clinical relevance. This article is protected by copyright. All rights reserved.
Offshore wind energy is getting increasing attention as a clean alternative to the currently scarce fossil fuels mainly used in Europe’s electricity supply. The further development and implementation of this kind of technology will help fighting global warming, allowing a more sustainable and decarbonized power generation. In this sense, the integration of Floating Offshore Wind Turbines (FOWTs) with Oscillating Water Columns (OWCs) devices arise as a promising solution for hybrid renewable energy production. In these systems, OWC modules are employed not only for wave energy generation but also for FOWTs stabilization and cost-efficiency. Nevertheless, analyzing and understanding the aero-hydro-servo-elastic floating structure control performance composes an intricate and challenging task. Even more, given the dynamical complexity increase that involves the incorporation of OWCs within the FOWT platform. In this regard, although some time and frequency domain models have been developed, they are complex, computationally inefficient and not suitable for neither real-time nor feedback control. In this context, this work presents a novel control-oriented regressive model for hybrid FOWT-OWCs platforms. The main objective is to take advantage of the predictive and forecasting capabilities of the deep-layered artificial neural networks (ANNs), jointly with their computational simplicity, to develop a feasible control-oriented and lightweight model compared to the aforementioned complex dynamical models. In order to achieve this objective, a deep-layered ANN model has been designed and trained to match the hybrid platform’s structural performance. Then, the obtained scheme has been benchmarked against standard Multisurf-Wamit-FAST 5MW FOWT output data for different challenging scenarios in order to validate the model. The results demonstrate the adequate performance and accuracy of the proposed ANN control-oriented model, providing a great alternative for complex non-linear models traditionally used and allowing the implementation of advanced control schemes in a computationally convenient, straightforward, and easy way.
We present in this paper a simple method to produce strategic acoustic particle capture sites in microfluidic channels in a controlled way. Air bubbles are intermittently injected into a micro-capillary with rectangular cross section during a flow motion of liquid suspensions containing micron-sized particles or particles to create bubble-defined “micro-gaps” with size close to 200 µm and spheroidal geometry. The establishment of a 3D standing acoustic wave inside the capillary at a frequency close to 1 MHz produces different radiation forces on solid particles and bubbles, and acoustic streaming around the bubble. While the sample flows, part of the particles collect along the acoustic pressure node established near the central axis and continue circulating aligned through the capillary until reaching the end, where are released enriched. Meanwhile, the bubble travels very fast toward positions of maximum pressure amplitude beside the channel wall, driven by Bjerkness forces, and attach to it, remaining immovable during the acoustic actuation. Some particles adhere to its membrane trapped by the acoustic streaming generated around the oscillating bubble. Changes of frequency were applied to analyze the influence of this parameter on the bubble dynamics, which shows a complete stability once attached to the channel wall. Only increasing the flow motion induces the bubble displacements. Once reached the open air at the end of the capillary, the bubble disappears releasing the trapped particles separated from their initial host suspension with a purity degree. The device presents a very simple geometry and a low-cost fabrication.
Institution pages aggregate content on ResearchGate related to an institution. The members listed on this page have self-identified as being affiliated with this institution. Publications listed on this page were identified by our algorithms as relating to this institution. This page was not created or approved by the institution. If you represent an institution and have questions about these pages or wish to report inaccurate content, you can contact us here.