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A Monte Carlo code for the collisional evolution of porous aggregates (CPA)
No full textContext. The collisional evolution of submillimeter-sized porous dust aggregates is important in many astrophysical fields.Aims. We have developed a Monte Carlo code to study the processes of collision between mass-asymmetric, spherical, micron-sized porous silica aggregates that belong to a dust population.Methods. The Collision of Porous Aggregates (CPA) code simulates collision chains in a population of dust aggregates that have different sizes, masses, and porosities. We start from an initial distribution of granular aggregate sizes and assume some collision velocity distribution. In particular, for this study we used a random size distribution and a Maxwell-Boltzmann velocity distribution. A set of successive random collisions between pairs of aggregates form a single collision chain. The mass ratio, filling factor, and impact velocity influence the outcome of the collision between two aggregates. We averaged hundreds of thousands of independent collision chains to obtain the final, average distributions of aggregates.Results. We generated and studied four final distributions (F), for size (n), radius (R), porosity, and mass-porosity distributions, for a relatively low number of collisions. In general, there is a profuse generation of monomers and small clusters, with a distribution F (R) proportional to R-6 for small aggregates. Collisional growth of a few very large clusters is also observed. Collisions lead to a significant compaction of the dust population, as expected.Conclusions. The CPA code models the collisional evolution of a dust population and incorporates some novel features, such as the inclusion of mass-asymmetric aggregates (covering a wide range of aggregate radii), inter-granular friction, and the influence of porosity.B.P., E.M., and E.M.B. acknowledge support from ANPCyT PICTO-UUMM-2019-00048 and SIIP 06/M008-T1. This work used the Toko Cluster from FCEN, UNCuyo, which is part of the SNCAD, MinCyT, Argentina
Machine learning modeling for the prediction of plastic properties in metallic glasses
No full textMetallic glasses are one of the most interesting mechanical materials studied in the last years, but as amorphous solids, they differ strongly from their crystalline counterparts. This matter can be addressed with the development and application of predictive techniques capable to describe the plastic regime. Here, machine learning models were employed for the prediction of plastic properties in CuZr metallic glasses. To this aim, 100 different samples were subjected to tensile tests by means of molecular dynamics simulations. A total of 17 materials properties were calculated and explored using statistical analysis. Strong correlations were found for stoichiometry, temperature, structural, and elastic properties with plastic properties. Three regression models were employed for the prediction of six plastic properties. Linear and Ridge regressions delivered the better prediction capability, with coefficients of determination above similar to 80% for three plastic properties, whereas Lasso regression rendered lower performance, with coefficients of determination above similar to 60% for two plastic properties. Overall, our work shows that molecular dynamics simulations together with machine learning models can provide a framework for the prediction of plastic behavior of complex materials.Authors thanks the Fondo Nacional de Desarrollo Cientifico y Tecnologico (FONDECYT, Chile) under grants #11200038 (NA), #1190662 and #11190484 (FV). FV thanks the Financiamiento Basal para Centros Cientificos y Tecnologicos de Excelencia AFB180001 and AFB220001. Powered@NLHPC: This research was partially supported by the supercomputing infrastructure of the NLHPC (ECM-02)
Effects of interventions on fundamental motor skills and physical activity in preschoolers: Systematic review
No full textPreescolares con mayor desarrollo de habilidades motoras fundamentales (HMF) se relaciona con mayor tiempo en actividad fÃsica (AF). Sin embargo, se sabe poco acerca de si la participación después de una intervención provoca cambios positivos en HMF y AF en edad preescolar. El objetivo de este artÃculo es analizar la evidencia publicada sobre la efectividad de intervenciones sobre HMF y AF en preescolares. Se realizaron búsquedas en cuatro bases de datos (Pubmed, Sportsdiscus, Web of Science y Psycinfo). Se incluyeron estudios publicados entre 2017 al 2021. Se incluyó estudios que consideran preescolares (3 a 6 años); diseño de estudio experimentales que implementarán una intervención; evaluar e informar las habilidades motoras fundamentales y actividad fÃsica y reportar asociaciones entre habilidades motoras fundamentales y actividad fÃsica. Un total de 4 estudios fueron incluidos con fuerte nivel de evidencia que apoya que las intervenciones mejoran las habilidades motoras fundamentales y una mayor participación en actividad fÃsica. Un estudio no observó cambios en el grupo experimental en la actividad fÃsica. Las intervenciones en preescolares podrÃa ser un enfoque eficaz para mejorar las habilidades motoras fundamentales y actividad fÃsica; sin embargo, es necesario completar más estudios con protocolos de intervenciones estandarizados
Continuous bioreactors enable high-level bioremediation of diesel-contaminated seawater at low and mesophilic temperatures using Antarctic bacterial consortia: Pollutant analysis and microbial community composition
No full textIn 2020, more than 21,000 tons of diesel oil were released accidently into the environment with most of it contaminating water bodies. There is an urgent need for sustainable technologies to clean up rivers and oceans to protect wildlife and human health. One solution is harnessing the power of bacterial consortia; however isolated microbes from different environments have shown low diesel bioremediation rates in seawater thus far. An outstanding question is whether Antarctic microorganisms that thrive in environments polluted with hydro-carbons exhibit better diesel degrading activities when propagated at higher temperatures than those encoun-tered in their natural ecosystems.Here, we isolated bacterial consortia, LR-30 (30 degrees C) and LR-10 (10 degrees C), from the Antarctic rhizosphere soil of Deschampsia antarctica (Livingston Island), that used diesel oil as the only carbon substrate. We found that LR-30 and LR-10 batch bioreactors metabolized nearly the entire diesel content when the initial concentration was 10 (g/L) in seawater. Increasing the initial diesel concentration to 50 gDiesel/L, LR-30 and LR-10 bioconverted 33.4 and 31.2 gDiesel/L in 7 days, respectively. The 16S rRNA gene sequencing profiles revealed that the dominant bacterial genera of the inoculated LR-30 community were Achromobacter (50.6%), Pseudomonas (25%) and Rhodanobacter (14.9%), whereas for LR-10 were Pseudomonas (58%), Candidimonas (10.3%) and Renibacterium (7.8%). We also established continuous bioreactors for diesel biodegradation where LR-30 bioremediated diesel at an unprecedent rate of (34.4 g/L per day), while LR-10 achieved (24.5 g/L per day) at 10 degrees C for one month. The abundance of each bacterial genera present significantly fluctuated at some point during the diesel biore-mediation process, yet Achromobacter and Pseudomonas were the most abundant member at the end of the batch and continuous bioreactors for LR-30 and LR-10, respectively.This work was founded by ANID-PIA-ANILLO INACH ACT-192057, FONDECYT 1200834, FONDECYT 1210332, INACH RG_21_18, INACH RG_17_19, FONDECYT 1210946, and INACH RT_12_17
Insights into early evolutionary adaptations of the Akkermansia genus to the vertebrate gut
No full textAkkermansia, a relevant mucin degrader from the vertebrate gut microbiota, is a member of the deeply branched Verrucomicrobiota, as well as the only known member of this phylum to be described as inhabitants of the gut. Only a few Akkermansia species have been officially described so far, although there is genomic evidence addressing the existence of more species-level variants for this genus. This niche specialization makes Akkermansia an interesting model for studying the evolution of microorganisms to their adaptation to the gastrointestinal tract environment, including which kind of functions were gained when the Akkermansia genus originated or how the evolutionary pressure functions over those genes. In order to gain more insight into Akkermansia adaptations to the gastrointestinal tract niche, we performed a phylogenomic analysis of 367 high-quality Akkermansia isolates and metagenome-assembled genomes, in addition to other members of Verrucomicrobiota. This work was focused on three aspects: the definition of Akkermansia genomic species clusters and the calculation and functional characterization of the pangenome for the most represented species; the evolutionary relationship between Akkermansia and their closest relatives from Verrucomicrobiota, defining the gene families which were gained or lost during the emergence of the last Akkermansia common ancestor (LAkkCA) and; the evaluation of the evolutionary pressure metrics for each relevant gene family of main Akkermansia species. This analysis found 25 Akkermansia genomic species clusters distributed in two main clades, divergent from their non-Akkermansia relatives. Pangenome analyses suggest that Akkermansia species have open pangenomes, and the gene gain/loss model indicates that genes associated with mucin degradation (both glycoside hydrolases and peptidases), (micro)aerobic metabolism, surface interaction, and adhesion were part of LAkkCA. Specifically, mucin degradation is a very ancestral innovation involved in the origin of Akkermansia. Horizontal gene transfer detection suggests that Akkermansia could receive genes mostly from unknown sources or from other Gram-negative gut bacteria. Evolutionary metrics suggest that Akkemansia species evolved differently, and even some conserved genes suffered different evolutionary pressures among clades. These results suggest a complex evolutionary landscape of the genus and indicate that mucin degradation could be an essential feature in Akkermansia evolution as a symbiotic species.The authors want to thank Jose Luis Maturana for his contributions in the early stage of this project.r JC was supported by ANID Fondecyt Project #11200209. BV-V was supported by ANID Doctorado Nacional/2021-21211564
Temporal Differences In The Myoelectric Activity Of Lower Limb Muscles During Rearfoot And Forefoot Running: A Statistical Parametric Mapping Approach
No full textDo Exotic Plants And Flower Colour Facilitate Bumblebee Invasion? Insights From Citizen Science Data
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