Optimizing Laser Powder Bed Fusion Parameters for IN-738LC by Response Surface Method

A method to find the optimum process parameters for manufacturing nickel-based superalloy Inconel 738LC by laser powder bed fusion (LPBF) technology is presented. This material is known to form cracks during its processing by LPBF technology; thus, process parameters have to be optimized to get a high quality product. In this work, the objective of the optimization was to obtain samples with fewer pores and cracks. A design of experiments (DoE) technique was implemented to define the reduced set of samples. Each sample was manufactured by LPBF with a specific combination of laser power, laser scan speed, hatch distance and scan strategy parameters. Using the porosity and crack density results obtained from the DoE samples, quadratic models were fitted, which allowed identifying the optimal working point by applying the response surface method (RSM). Finally, five samples with the predicted optimal processing parameters were fabricated. The examination of these samples showed that it was possible to manufacture IN738LC samples free of cracks and with a porosity percentage below 0.1%. Therefore, it was demonstrated that RSM is suitable for obtaining optimum process parameters for IN738LC alloy manufacturing by LPBF technology.This research was funded by Elkartek programme, grant number KK-2018/00115, which is part of the Economic Development Department of the Basque Country Government

High Hg biomagnification in North Atlantic coast ecosystems and limits to the use of δ15N to estimate trophic magnification factors

Mercury contamination is a global environmental problem. This pollutant is highly toxic and persistent which makes it extremely susceptible to biomagnify, i.e. increase its concentrations as it moves up the food chain, reaching levels that threaten wildlife and, ultimately, ecosystems’ function and structure. Mercury monitoring is thus crucial to determine its potential to damage the environment. In this study, we assessed the temporal trends of the concentrations of Hg in two coastal animal species closely connected by a predator-prey interaction, and evaluated its potential transfer between trophic levels using the δ15N signatures of the two species. For this, we performed a multi-year survey of the concentrations of total Hg and the values of δ15N in the mussel Mytilus galloprovincialis (prey) and the dogwhelk Nucella lapillus (predator) sampled along ∼1500 km of the North Atlantic coast of Spain over a 30-year period (five surveys between 1990 and 2021). Concentrations of Hg decreased significantly between the first and the last survey in the two species studied. Except for the 1990 survey, the concentrations of Hg in mussels were amongst the lowest registered in the literature for the North East Atlantic Ocean (NEAO) and the Mediterranean Sea (MS) between 1985 and 2020. Nonetheless, we detected Hg biomagnification in almost all surveys. Worryingly, trophic magnification factors obtained here for total Hg were high and comparable to the found in the literature for methylmercury, the most toxic and readily biomagnified form of this element. The δ15N values were useful to detect Hg biomagnification under normal circumstances. However, we found that nitrogen pollution of coastal waters differentially affected the δ15N signatures of mussels and dogwhelks limiting the use of this parameter for this purpose. We conclude that Hg biomagnification could constitute an important environmental hazard even when found at very low concentrations in the lower trophic levels. Also, we warn that use of δ15N in biomagnification studies when there is some underlying nitrogen pollution problem might lead to misleading conclusionsAuthors belong to the Grupo de Referencia Competitiva GRC GI-1252/GPC2020–23 (ED431C 2020/19) which is co-funded by Xunta de Galicia and ERDF (EU)S

Identification of West Nile virus RNA-dependent RNA polymerase non-nucleoside inhibitors by real-time high throughput fluorescence screening

West Nile virus (WNV) is a re-emergent mosquito-borne RNA virus that causes major outbreaks of encephalitis around the world. However, there is no therapeutic treatment to struggle against WNV, and the current treatment relies on alleviating symptoms. Therefore, due to the threat virus poses to animal and human health, there is an urgent need to come up with fast strategies to identify and assess effective antiviral compounds. A relevant target when developing drugs against RNA viruses is the viral RNA-dependent RNA polymerase (RdRp), responsible for the replication of the viral genome within a host cell. RdRps are key therapeutic targets based on their specificity for RNA and their essential role in the propagation of the infection. We have developed a fluorescence-based method to measure WNV RdRp activity in a fast and reliable real-time way. Interestingly, rilpivirine has shown in our assay inhibition of the WNV RdRp activity with an IC50 value of 3.3 μM and its antiviral activity was confirmed in cell cultures. Furthermore, this method has been extended to build up a high-throughput screening platform to identify WNV polymerase inhibitors. By screening a small chemical library, novel RdRp inhibitors 1–4 have been identified. When their antiviral activity was tested against WNV in cell culture, 4 exhibited an EC50 value of 2.5 μM and a selective index of 12.3. Thus, rilpivirine shows up as an interesting candidate for repurposing against flavivirus. Moreover, the here reported method allows the rapid identification of new WNV RdRp inhibitors

BioTIME: A database of biodiversity time series for the Anthropocene.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Adsorptive of Nickel in Wastewater by Olive Stone Waste: Optimization through Multi-Response Surface Methodology Using Desirability Functions

Pollution from industrial wastewater has the greatest impact on the environment due to the wide variety of wastes and materials that water can contain. These include heavy metals. Some of the technologies that are used to remove heavy metals from industrial effluents are inadequate, because they cannot reduce their concentration of the former to below the discharge limits. Biosorption technology has demonstrated its potential in recent years as an alternative for this type of application. This paper examines the biosorption process for the removal of nickel ions that are present in wastewater using olive stone waste as the biosorbent. Kinetic studies were conducted to investigate the biosorbent dosage, pH of the solution, and stirring speed. These are input variables that are frequently used to determine the efficiency of the adsorption process. This paper describes an effort to identify regression models, in which the biosorption process variables are related to the process output (i.e., the removal efficiency). It uses the Response Surface Method (RSM) and it is based on Box Benken Design experiments (BBD), in which olive stones serves as the biosorbent. Several scenarios of biosorption were proposed and demonstrated by use of the Multi-Response Surface (MRS) and desirability functions. The optimum conditions that were necessary to remove nickel when the dosage of biosorbent was the minimum (0.553 g/L) were determined to be a stirring speed of 199.234 rpm and a pH of 6.369. The maximum removal of nickel under optimized conditions was 61.73%. Therefore, the olive stone waste that was investigated has the potential to provide an inexpensive biosorbent material for use in recovering the water that the nickel has contaminated. The experimental results agree closely with what the regression models have provided. This confirms the use of MRS since this technique and enables satisfactory predictions with use of the least possible amount of experimental data

Finite Element Model Updating Combined with Multi-Response Optimization for Hyper-Elastic Materials Characterization

The experimental stress-strain curves from the standardized tests of Tensile, Plane Stress, Compression, Volumetric Compression, and Shear, are normally used to obtain the invariant &#955;i and constants of material Ci that will define the behavior elastomers. Obtaining these experimental curves requires the use of expensive and complex experimental equipment. For years, a direct method called model updating, which is based on the combination of parameterized finite element (FE) models and experimental force-displacement curves, which are simpler and more economical than stress-strain curves, has been used to obtain the Ci constants. Model updating has the disadvantage of requiring a high computational cost when it is used without the support of any known optimization method or when the number of standardized tests and required Ci constants is high. This paper proposes a methodology that combines the model updating method, the mentioned standardized tests and the multi-response surface method (MRS) with desirability functions to automatically determine the most appropriate Ci constants for modeling the behavior of a group of elastomers. For each standardized test, quadratic regression models were generated for modeling the error functions (ER), which represent the distance between the force-displacement curves that were obtained experimentally and those that were obtained by means of the parameterized FE models. The process of adjusting each Ci constant was carried out with desirability functions, considering the same value of importance for all of the standardized tests. As a practical example, the proposed methodology was validated with the following elastomers: nitrile butadiene rubber (NBR), ethylene-vinyl acetate (EVA), styrene butadiene rubber (SBR) and polyurethane (PUR). Mooney&#8211;Rivlin, Ogden, Arruda&#8211;Boyce and Gent were considered as the hyper-elastic models for modeling the mechanical behavior of the mentioned elastomers. The validation results, after the Ci parameters were adjusted, showed that the Mooney&#8211;Rivlin model was the hyper-elastic model that has the least error of all materials studied (MAEnorm = 0.054 for NBR, MAEnorm = 0.127 for NBR, MAEnorm = 0.116 for EVA and MAEnorm = 0.061 for NBR). The small error obtained in the adjustment of the Ci constants, as well as the computational cost of new materials, suggests that the methodology that this paper proposes could be a simpler and more economical alternative to use to obtain the optimal Ci constants of any type of elastomer than other more sophisticated methods

Campaña extra de verano de la ONCE

A continuación se presenta un resumen de lo que trata este Trabajo de fin de grado. Nuestro trabajo consiste en simular como sería el proceso completo de una agencia de publicidad a la hora de realizar una campaña publicitaria. Nosotros, actuando como agencia, recibimos un briefing para anunciar el “sorteo del extra de verano de la ONCE”. Para realizar esta simulación con la mayor precisión posible seguiremos todos los pasos que hemos ido aprendiendo a lo largo de la carrera. Todos estos pasos serán tutorizados por un profesor del grado, de cara a conseguir la mayor precisión posible. Estos pasos que llevaremos a cabo tienen un orden cronológico de realización, este será el siguiente; investigación, ideación y por último la creación de la campaña. De cara a poder mostrar y conseguir una simulación más completa, trataremos de crear por medio de bocetos y guiones como sería el resultado de la campaña. Es importante recalcar que estamos trabajando con un tipo de publicidad muy característico de nuestro cliente, la publicidad social. Esto plantea un reto para el trabajo, vender un producto sin dejar de lado las preocupaciones sociales por las que tanto ha luchado y por las que se caracteriza la ONCE.Grado en Publicidad y Relaciones Pública

Coagulation: Determination of Key Operating Parameters by Multi-Response Surface Methodology Using Desirability Functions

The clarification process removes colloidal particles that are suspended in waste water. The efficiency of this process is influenced by a series of inputs or parameters of the coagulation process, of which the most commonly used are initial turbidity, natural coagulant dosage, temperature, mixing speed and mixing time. The estimation of the natural coagulant dosage that is required to effectively remove these total suspended solids is usually determined by a jar test. This test seeks to achieve the highest efficiency of removal of the total suspended solids while reducing the final turbidity of waste water. This is often configured in iterative fashion, and requires significant experimentation and coagulant. This paper seeks to identify regression models that relate the clarification process parameters to the process outputs (final turbidity and total suspend solid) by the Response Surface Methodology (RSM) based on experiments of Central Composite Design (CCD) of experiments that involve three emerging natural coagulants. Several clarification process scenarios also were proposed and demonstrated using the Multi-Response Surface (MRS) with desirability functions. The experimental results were found to be in close agreement to what are provided by the regression models. This validates the use of the MRS-based methodology to achieve satisfactory predictions after minimal experimentation