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Muonic x-ray spectroscopy uses muons to obtain information about the structure of the atom and the nucleus. In muonic atoms, the energy levels of atomic orbitals are significantly more sensitive to the finite size correction. By probing these orbitals using x-ray spectroscopy, the nuclear size correction can be extracted, providing valuable input for laser spectroscopy in the form of absolute charge radii with a relative precision better than 10−3. Continuing on developments that allowed measurements on target quantities of about 5 μg, we showed the feasibility of using implanted targets. In the future, this will allow the measurement of absolute charge radii of long-lived radioactive isotopes that are not available in sufficient enrichment or large quantities. In this contribution, we shall report on the target preparation, involving high-fluence implantation, and on the preliminary results of the muX experimental campaign. ISSN:0168-583X ISSN:1872-9584

Resveratrol is a natural phytoalexin present in human diet with a potential beneficial effect in many diseases including chronic and acute pancreatitis, a potentially fatal disease with significant morbimortality accompanied with obscure pathogenesis and without effective treatments. Resveratrol has also been shown to be a promising anti-tumor molecule on the millimolar scale. In this study, the protective effects of nanomolar concentrations of resveratrol against early events common to pancreatic cancer and pancreatitis induced by supra-physiological concentrations of cholecystokinin (CCK, 100 nM) were evaluated. Resveratrol (200, 500 nM) reduced CCK-induced intracellular trypsin activation and cell injury in isolated rat pancreatic acinar cells (PAC). The damage induced by high CCK and the protective effect of resveratrol was also measured in pancreatic tissue explants by analyzing histological changes. Finally, the effect of resveratrol on the CCK-enhanced nuclear factor κB (NF-κB) expression was studied by Western blot experiments in the AR42J pancreatic acinar cell line. Our results show, for the first time, the ability of resveratrol to reduce premature intracellular activation of trypsin and necrosis in PAC. It is suggested that resveratrol counteracts CCK-induced pancreatic tissue breakdown by downregulation of NF-κB in the nuclear fraction. Since these effects occur at nanomolar concentrations that can be achieved by oral intake, our results suggest that dietary consumption of resveratrol could have a preventive effect and delay the evolution of pancreatitis and pancreatic cancer.

Despite growing interest in developing extensive fuel treatment programs to prevent catastrophic wildfires in the Mediterranean region, there is little information on the projected effectiveness of fuel treatments in terms of avoided exposure and risk. In Portugal, a fuel management plan aiming to prevent loss of lives, reduce large fires (500 ha), and reduce annual burned area is under implementation, with particular emphasis on the nation-wide fuel break network (FBN). In this study, we evaluated the effectiveness of the planned FBN in terms of meeting fire management objectives, costs, and benefits. We first estimated the overall effectiveness of the FBN at intersecting modeled large fires (500 ha) and at reducing exposure to protected areas and residential buildings using wildfire simulation modeling. Then, the fuel break burn-over percentage, i.e. the percentage of fires that are not contained at the FBN, was modeled as a function of pre-defined flame length thresholds for individual FBN segments. For the planned FBN, the results suggested a potential reduction of up to 13% in the annual burned area due to large fires (ca. 13,000 ha), of up to 8% in the annual number of residential buildings exposed (ca. 100 residential buildings), and up to 14% in the annual burned area in protected areas (ca. 2400 ha). The expected burn-over percentage was highly variable among the segments in response to estimated fire intensity, and an average decrease of 40% of the total benefits was estimated. The most important fuel breaks typically showed a higher percentage of fire burn-over, and hence reduction in effectiveness. We also showed that the current implementation of FBN follows a random sequence, suboptimal for all objectives. Our results suggest that additional landscape-scale fuel reduction strategies are required to meet short-term national wildfire management targets.

The Iberian Peninsula is recurrently affected by devastating wildfires that result from an interplay of human activities, landscape features, and atmospheric conditions. The fact that the Mediterranean basin, and the Iberian Peninsula in particular, is a hotspot of climate change, strongly suggests that particular attention should be devoted to the role played by atmospheric conditions on wildfire activity.Here we present a statistical model that is able to simulate the probability of occurrence of a fire event that releases a given amount of Fire Radiative Power, provided a specified level of meteorological fire danger as rated by the Fire Weather Index.The model combines a lognormal distribution central body with a lower and an upper tail, both consisting of Generalized Pareto (GP) distributions, and daily FWI is used as a covariate of the parameters of the lognormal and the two GP distributions.The Iberian Peninsula is subdivided into four spatially homogeneous pyro-regions, namely the northwest(NW), southwest (SW), north (N) and east (E) regions. Fire data cover the period 2001-2020 and consist of Fire Radiative Power (FRP) as acquired by the MODIS instrument on-board Aqua and Terra Satellites. Fire Weather (FWI) data covering the same period were obtained from the Copernicus Emergency Management Service.For each region, the statistical model is fitted to the sample of FRP of all recorded events. First a base model (with fixed parameters) is fitted to the decimal logarithm of FRP, and the quality of fit is assessed using an Anderson-Darling test. Then the model is improved using FWI as a covariate, and performances of models without and with covariate are compared by computing the Bayes Factor as well as by applying the Vuong’s closeness test.For each region, a set of 100 synthetic time series of total annual FRP is set up using the statistical models without and with FWI as a covariate. This is achieved by randomly generating probabilities for each observed event, generating the FRP associated to that probability and then adding up the generated FRP all events for each year. The interannual variability of synthetic time series obtained is then compared with the corresponding interannual variability of the recorded events.Results obtained for region SW show an increase from 91 to 96% of interannual explained variance of FRP when going from the model without to the model with FWI. Increases from 95 to 96%, 84 to 90% and from 78 to 86% were obtained for regions NW, N and E. It is worth stressing that these are conservative estimates of change since the dependence of number of ignitions on FWI was not taken into account. This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project FIRECAST (PCIF/GRF/0204/2017).

Flash-pulzní termografické nedestruktivní testování je často používaná technika pro inspekci kompozitních materiálů.Tato studie je zaměřena na statistické hodnocení flash-pulzní termografické metody při nedestruktivním testování kompozitních materiálů. Referenční vzorky z kompozitního materiálu s 50 umělými defekty byly testovány 3 operátory ve 2 nezávislých kolech. Hodnocení indikací bylo provedeno na základě hodnoty kontrastu indikací vůči okolí (contrast to noise ratio) a na základě zjištěné velikosti indikací. Bylo zjištěno, že při daných podmínkách je celková Gage R&R variabilita 23 % a 45 % pro průměr resp. pro kontrast indikace. Thermographic flash-pulse inspection is a popular technique of non-destructive testing (NDT) of carbon-fiber composites. Despite of an automation of the NDT methods, most of them are based on a visual inspection of indications and results of the inspections are thus influenced by the skills of operators. Repeatability and reproducibility (R&R) analysis of these inspections are therefore more important than in the case of exact gauge-type methods. This study was focused on statistical evaluation of flash pulse inspection. Space hardware representative carbon-fiber composite samples with 50 artificial defects were used as reference samples, which were independently inspected by three operators in two independent runs.Gauge R&R study was performed based on contrast to noise ratio and size of defects indications. It was determined, that, at certain conditions, a total Gage R&R variability 23% and 45% can be achieved for the diameter and the contrast to noise ratio evaluation, respectively

In this work, conducted by three partners (UFAM/CETELI, ICTS and ENVISION/TPV), we developed practical experiment scenarios, showing the viability of creating QoE assessment scenarios for 4k videos, using off-the-shelf computers equipped with GPU, software free and transmission over WiFi networks. We evaluated a set of 4 unreferenced QoE metrics, noting that videos transmitted via WiFi have QoE similar to the original, untranslated video.

In recent years, the number of Wi-fi networks has been growing and the coexistence of Wi-fi networks can produce interference causing connection difficulties. Light communication is getting more popular with a large numbers of studies. In this work conducted by three partners (UFAM/CETELI, ICTS and ENVISION/TPV), we propose a multimedia model for wireless communication using light. This propose is based in off-the-shelf devices in the current market to establish an operational model of multimedia transmission for videos in 4k . In addition, modeling for the communication channel is addressed.

In this work, conducted by three partners (UFAM/CETELI, ICTS and ENVISION/TPV), we created practical experiment scenarios, showing the viability of creating 4k video QoE assessment scenarios, using off-the-shelf computers equipped with GPU, software free and transmission in WiFi networks. In the evaluation, we used a set of 7 metrics of QoE verifying that videos transmitted via WiFi have QoE similar to the original video, not transmitted.

The acquisition of sophisticated vector signal analyzer (VSA) may be a limiting factor for the execution of RD (ii) spectral flatness; (iii) transmitter constellation error; (iv) transmitter modulation accuracy (EVM). The results indicates that this approach is a feasible VSA solution for R&D projects with budget limitations.

The internal flow in corrugated tubes of different helical pitch, covering from the laminar to turbulent regime, was studied in order to characterize the three-dimensional flow and the influence of corrugation geometry on pressure drop and convective heat transfer. With water as working fluid and an imposed wall heat flux, ranging from around 4 to 33 kW/m2, a numerical model was developed with a CFD commercial software, where k-omega SST was used to model turbulence. Experimental tests were performed covering Reynolds numbers in the range from around 300 up to 5000, which allowed to identify the transition region and validate the numerical model. The results show that due to the swirl induced by the corrugation, the critical Reynolds number for the start of transition to turbulent flow is reduced. The thermal performance factor, which quantifies the heat transfer enhancement at the expense of pressure drop, was used to compare the corrugated tubes against the reference case of smooth tube. Based on this, all investigated corrugated geometries performed better than the smooth tube, except for low Reynolds numbers (Re, Comment: 15 pages, 15 figures

The present work deals with the numerical simulations of 3D incompressible flow through periodic porous structures, consisting of cubic cells with different strut geometry and structure tilting with respect to the flow direction. Simulation results are obtained for different porosities, while covering a range of Reynolds numbers from laminar-steady flow (Darcy regime) up to the transition to laminar-unsteady flow (moderate Forchheimer regime). These results are post-processed in order to characterize the influence of the periodic porous structures on the flow statistics related to the Darcy-Forchheimer law. Based on this analysis, along with 3D simulation results previously obtained for different random foams, correlations for the Darcy and Forchheimmer permeability coefficients are developed from a theoretical background, being expressed only as functions of the cell geometrical parameters and tortuosity estimation. However, the influences of flow tortuosity and cell orientation on the Darcy coefficient are found to cancel each other. The proposed correlation for the Darcy coefficient performs very well for both periodic and random porous structures, when compared with recent correlations available in the literature. The performance of the correlation proposed for the Forchheimmer coefficient is found to be satisfactory, however, different correlation constants were found for periodic and random structures. The proposed correlation for the Forchheimer permeability coefficient depends on the flow tortuosity inside the porous structure, which must be estimated either through 3D fluid flow simulations or using tortuosity correlations. In this respect, a correlation is proposed for predicting the flow tortuosity inside porous structures, as an alternative for avoiding 3D simulations.

Mura on LCD displays are challenging visual defects to detect, due to uneven brightness of the panel. So, automatic detection of mura defects on TVs and monitors is an important application to ensure the quality of LCDs manufactured in electronic product factories. In this work, conducted by three partners, called UFAM/CETELI, Envision (TPV Group) and ICTS, we propose an automated mura defect detection system on LCD displays that are based on similarities of the histograms and a machine learning (ML) algorithm called random forest. For comparison with the proposed method, we use one of the most popular methods of ML called k-Nearest Neighbors (k-NN). The experimental results show a detection rate above 99%, and processing time of 27 milliseconds per image, highlighting as contributions of our proposal, the high accuracy and reduced processing time, which allows the use of our solution in real production processes of LCD monitors.

Bright pixel defect occurs in LCDs when a transistor of a subpixel remains bright. Bright pixels reduce the quality of manufactured devices, negatively impacting companies looking to meet an increasingly demanding market. In this wokr, conducted by three partners, called UFAM/CETELI, Envision (TPV Group) and ICTS, we propose an automated bright pixel defect detection system on LCD displays, which works in conjunction with two proposed methods, the quartile-based method and the standard-based method to identify bright pixels in LCDs. The proposals obtained as best result 100% of accuracy and between 0.397s and 0.193s of average processing time per image. The results of high accuracy and reduced processing time demonstrate the contribution of our proposal, being possible to use it in the detection of bright pixels in real production lines that use LCDs on TVs or monitors.

In this contribution, we present some examples of how molecular modeling techniques (perturbation theory of complex fluids and molecular simulations) can help in reducing GHG emissions by applying them in cases where molecular information, thermophysical, and transport properties are needed to better design processes involving new refrigerants, aqueous amine solutions, and/or solid adsorbents for CO2 capture and separation. This work is part of a long-term project focused on developing general and reliable molecular models for the thermodynamic characterization of environmentally friendly systems, from their fundamental understanding to the design and optimization of the process.

Manufacturing TVs and monitors requires an effective method to detect the dead pixels. These defects are usually identified by operators manually. However, manual inspection is susceptible to failure due to human fatigue and generate a high cost for production process. In this work, conducted by three partners (UFAM/CETELI, ICTS and ENVISION/TPV), we propose three methods for automated detection of dead pixels. Two proposed methods were based on machine learning (ML) techniques, random forest (RF) and support vector machine (SVM) algorithms. The third method was based in digital image processing (DIP), Harris algorithm. As result, the SVM obtained the better performance with 92.1% of precision in two of three used image database.

semi-structured questionnaire was taken to investigate the knowledge level of inters about exposure in occupational risks with biological material and the prevention strategies. The 89 interns of Pharmacy and Dental School of Universidade Federal de Juiz de Fora were interviewed, and most of students reported to have the appropriate IPE and were also oriented in classes about the use of such equipment. The majority claimed to be aware of which diseases they were exposed, and Hepatitis and HIV were the most mentioned. However, there were some answers indicating unfamiliarity about the subject. In contrast, almost the totality of students reported vaccination against Hepatitis B. More than 50 % reported to know about the existence of a notification protocol at the institution, and also they knew how to notify, but 21 % (dentistry) 56% (pharmacy) denied the accessibility of the notification protocol, and in case of contamination.About if they have ever had an accident, 30% (dentistry) and 6% (pharmacy) answered “yes”, but not all exposures were affected diseases, notification importance and the preceptor in the practice setting, but also reveals that some of them do not know where the notification protocol is located and they were not satisfied with the obtained information after exposure. reported. The study highlights that respondents showed previous knowledge about the contamination risks of the main

The development of new amine systems for CO2 capture is a topic of high interest because of the limitations current aqueous amine systems have for capturing CO2 at large scale. Having a robust and systematic approach for describing the absorption of CO2 would help accelerating the discovery of high performance amine solvents. In this contribution, a molecular-based equation of state is applied to describe the absorption of CO2 in aqueous solutions of single and blended amines at conditions of relevance for post-combustion CO2 capture. A scheme of implicit reactions is used to describe the formation of carbamate and/or bicarbonate products resulting from the chemical reactions between CO2 and five amines of practical industrial interest. This procedure eliminates the need to specify the detailed equilibrium reactions and significantly reduces the number of parameters required to represent the absorption process. A maximum of two adjustable model parameters (one of which with a linear temperature dependence), optimised for a fixed amine concentration, suffices to represent the absorption of CO2 in aqueous solutions of single amines over a broad range of temperatures (298–413 K) and partial pressures of CO2 (0.1–1000 kPa). The extrapolation capabilities of the model are tested by predicting the absorption of CO2 in aqueous solutions of single amines for different amines concentrations (∼8.5–35 wt%), with modelling results showing good quantitative agreement with solubility, speciation and enthalpy of absorption data available in literature. Furthermore, without introducing any new model parameter, the absorption of CO2 in various amine blends is satisfactorily predicted by considering competing interactions for the reactive sites in the model of CO2. The developed models are then used to assess the CO2 capture performance of selected amine systems in terms of two key process parameters: solvent cyclic capacity and regeneration energy. Results for systems with the same total amine mass concentration show that the highest molar cyclic capacities are obtained for 30 wt% piperazine (0.45 mol CO 2 .mol Amine - 1 ), whereas the greatest energy savings for solvent regeneration are estimated for 30 wt% methyldiethanolamine (2.3 GJ .tCO 2 - 1 ). Moreover, two piperazine–promoted blends showed the potential for reducing up to ∼26% the energy consumption for solvent regeneration and separating up to ∼41% more CO2 in a molar basis when compared to the benchmark 30 wt% monoethanolamine. Altogether, these results demonstrate the feasibility of the developed approach as a reliable platform for the screening of amine solvents as function of key process parameters, and as a valuable tool for process modelling.

This work deals with stochastic calculations for the dynamics of granular flows in rotating cylindrical drums, using the discrete element method (DEM). The drum is 100 mm in diameter and 35% filled with 3-millimetrediameter spheres rotating at various speeds. The deterministic model is extensively validated through reported studies in terms of the dynamic repose angle and spatial velocity fields. The stochastic simulation study focuses on the uncertainties related to the physical particle characteristics that simultaneously influence the granular flow interactions, such as friction coefficients, restitution coefficients, Young's modulus, Poisson's ratios and others input parameters. The uncertainty propagation from the model input parameters to the output stochastic solution is quantified using non-intrusive chaos expansion. Throughout this work, the study focuses on the behaviour of particles within a rotating drum, as many industries use this type of configuration for their processes. This method allows for the determination of stochastic solutions from a set of deterministic simulations. The simulation variables (such as particle velocities and dynamic angles of repose) are characterized in terms of the stochastic mean, probability density function and error bar. For the uncertainty propagation, the random friction coefficient is the most dominant input variable for the granular flow dynamics in a horizontal drum.

The development of new alkanolamines/amines is a topic which has attracted a great deal research interest, particularly as absorbents for the removal of acid gases from industrial sources and CO2 capture applications. One of the major challenges when evaluating the techno-economic performance of selected new single amines or blends is the lack of experimental data on the thermophysical properties required for a reliable process design and simulation. In this contribution, a robust theoretical framework for the description of key thermophysical properties of aqueous solutions of single and mixed alkanolamines/amines at relevant gas separation process conditions is proposed. The approach is based on the coupling of the Free-Volume Theory and the Density Gradient Theory with a molecular-based equation of state (soft-SAFT) for the integrated modelling of phase behaviour, enthalpies, densities, viscosities and interfacial tensions. The alkanolamines and amines investigated differ in their family and structure, and included primary (monoethanolamine), secondary (diethanolamine), tertiary (methyldiethanolamine), sterically hindered (2-amino-2-methyl-1-propanol) and cyclic amines (piperazine). The study was performed in a systematic manner, starting from the development of the models for the pure amines, the description of their thermophysical properties, and the properties of the aqueous mixtures. Compared to other models described in literature, the present modelling approach preserves the effects due the chemical structure and key intermolecular interactions of the examined alkanolamines/amines through a set of molecular parameters obtained from pure substance data, whenever available, or transferred from substances of different chemical families. This enabled the development of a consistent modelling framework which can provide reliable thermodynamic property predictions of both single and blended amine solutions over a broad range of temperatures (298–373 K) and compositions (0–50 wt% amine). The proposed approach is well-suited for implementation and extension to other alkanolamines and amines, making it a valuable tool for having reliable process simulations as well as for the screening and discovery of new amine systems, which will be required for the deployment of more economical acid gas removal processes.

We present new experimental data on the isobaric vapor–liquid equilibria (VLE) of four binary mixtures of water with ethylene glycol, diethylene glycol, triethylene glycol, or tetraethylene glycol, measured at three different system pressures (0.05, 0.07, and 0.1 MPa). Water activity coefficients were estimated from the mixtures boiling temperatures and used to rationalize the effect of the increasing glycols chain length on the molecular interactions with water. The soft statistical associating fluid theory (SAFT) equation of state was used to describe the experimental VLE data of these highly nonideal systems, providing insights into the molecular interactions leading the macroscopic behavior of the mixtures. Glycols and water were both modeled as associating molecules, with models and parameters from previous works, in a transferable manner. Soft-SAFT accurately reproduces the experimental data using one single, state independent, binary interaction parameter to correct the mixtures dispersive energy. ...

A multiscale methodology combining three different reactor length-scales is presented to investigate the role of the catalyst internal pore structure and metal loading and dispersion on the catalyst layer and full-scale reactor performances. At the catalyst level, the methodology involves pore-scale simulations in the three-dimensional mesopore and macropore space. The information gathered at the catalyst level is delivered to the full-scale reactor model. The methodology is applied to a honeycomb reactor performing methane partial oxidation considering reaction kinetics described through a detailed multistep reaction mechanism. Realistic mesopore and macropore structures were reconstructed and combined to form specific bidisperse porous washcoat layers. The study shows that species effective diffusivities vary significantly but not in the same proportion for different structures. For structures featuring poor transport characteristics, the integral methane conversion and hydrogen selectivity are strongly affected while the reactor temperatures increase substantially. © 2017 American Institute of Chemical Engineers AIChE J, 64: 578–594, 2018

In this study the interfacial tension (IFT) between CO2 and brines, in the context of geological storage of CO2, was investigated. Investigations covered both experimental and theoretical aspects of this property over a broad range of conditions, including those found in subsurface formations. Measurements for CO2 + NaCl(aq) systems, of salt molalities 0.98 and 1.98 mol.kg-1, were performed for temperatures and pressures up to 423 K and 69.51 MPa, respectively. Results clearly showed an increase from CO2 + H2O IFT upon the addition of the salt, helping to resolve some discrepancies observed in literature data. Furthermore, a predictive method, based on the Density Gradient Theory, was extended to CO2 + brine systems, with modelled IFT values yielding a good agreement with experiments from this work and literature for brines of single and mixed salts, including NaCl, KCl and CaCl2, and ionic strength up to 2.7 mol.kg−1.

Thermal analysis and management studies are commonly conducted from early design stages of new products by numerical means. However, the application of three-dimensional tools for evaluating the thermal performance of multi-component systems, exhibiting high geometrical and phenomenological complexities may become unpractical in view of the long computational times. Therefore, a methodology for thermal analysis of complex thermal systems is developed to improve the overall numerical convergence rate. The methodology is based on an iterative two-way coupling procedure between two sets of simulations: simulation set where critical components are individual and fully simulated (component-level simulations); and simulation framework where the overall system is considered with hollow components (system-level simulation). A communication strategy between both simulation sets is established. The methodology can be readily applied for performing thermal management studies. A verification procedure for the suggested methodology is firstly carried out. Afterwards, the methodology is applied to investigate the thermal performance at the system-level of a fuel cell based μ - CHP unit, namely regarding the feasibility of components integration. The methodology application allowed the identification of critical hot-spots (with temperatures up to about 400 ° C ) on the surface of the unit internal components, mainly due to an inadequate insulation thickness and shape.