Predicting rainfall and irrigation requirements of corn in Ecuador.

This work is a case study whose objective is prediction of irrigation needs of corn crops in different regions of Ecuador; being this a fundamental basic food for the country's economy, as in the remaining countries of the Andean area. The proposed methodology seeks to help improving the quality of corn crop. Specifically, we propose the application of regression models, within the framework of Functional Data Analysis (FDA), to predict the amount of rainfall (scalar response variable) in the places with the highest production of corn in Ecuador, as a function of functional covariates such as temperature and wind speed.

TTS package: Computational tools for the application of the Time Temperature Superposition principle.

The TTS package has been developed in R software to predict the mechanical properties of viscoelastic materials, at short and long observation times/frequencies by applying the Time Temperature Superposition (TTS) principle. TTS is a physical principle used in material science to estimate mechanical properties beyond the experimental range of observed times/frequencies by shifting data curves obtained at other temperatures relative to a reference temperature in the dataset. It is a methodology related to accelerated life-tests and reliability, whereas the TTS library is one of the first open source computational tool to apply the TTS principle.

Considerations on the programmed functional life (one generation) of a green artificial reef in terms of the sustainability of the modified ecosystem.

The installation of artificial reefs serves to enhance marine ecosystems, although it also modifies them. These changes do not have to be irreversible, since it is possible to treat the functional life of an artificial reef (AR) as a variable factor to be determined, with the objective of contributing to the sustainability of the ecosystem. The quest for sustainability does not end with the manufacture and installation of the AR units.

Application of residuals from purification of bivalve molluscs in Galician to facilitate marine ecosystem resiliency through artificial reefs with shells - One generation.

The seas and oceans of the planet provide a wide range of essential resources. However, marine ecosystems are undergoing severe degradation due to the unsustainable exploitation and consumption patterns of the linear economy. On the other hand, many economic activities linked to the sea generate a large amount of waste, leading to negative impacts, such as the cost of treating or disposing of this waste.

Modeling the number of people infected with SARS-COV-2 from wastewater viral load in Northwest Spain.

The quantification of the SARS-CoV-2 RNA load in wastewater has emerged as a useful tool to monitor COVID-19 outbreaks in the community. This approach was implemented in the metropolitan area of A Coruña (NW Spain), where wastewater from a treatment plant was analyzed to track the epidemic dynamics in a population of 369,098 inhabitants. Viral load detected in the wastewater and the epidemiological data from A Coruña health system served as main sources for statistical models developing.

Evaluation of the Curing of Adhesive Systems by Rheological and Thermal Testing.

The analysis of thermal processes associated to the curing of adhesives and the study of mechanical behavior once cured, provide key information to choose the best option for any specific application. The proposed methodology for the curing characterization, based on thermal analysis and rheology, is described through the comparison of three commercial adhesives. The experimental techniques used here are Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC) and Rheology.

An artificial-vision- and statistical-learning-based method for studying the biodegradation of type I collagen scaffolds in bone regeneration systems.

This work proposes a method based on image analysis and machine and statistical learning to model and estimate osteocyte growth (in type I collagen scaffolds for bone regeneration systems) and the collagen degradation degree due to cellular growth. To achieve these aims, the mass of collagen -subjected to the action of osteocyte growth and differentiation from stem cells- was measured on 3 days during each of 2 months, under conditions simulating a tissue in the human body. In addition, optical microscopy was applied to obtain information about cellular growth, cellular differentiation, and collagen degradation.

Correction: Statistical degradation modelling of Poly(D,L-lactide-co-glycolide) copolymers for bioscaffold applications.

[This corrects the article DOI: 10.1371/journal.pone.

Statistical degradation modelling of Poly(D,L-lactide-co-glycolide) copolymers for bioscaffold applications.

This methodology permits to simulate the performance of different Poly(D,L-lactide-co-glycolide) copolymer formulations (PDLGA) in the human body, to identify the more influencing variables on hydrolytic degradation and, thus, to estimate biopolymer degradation level. The PDLGA characteristic degradation trends, caused by hydrolysis processes, have been studied to define their future biomedical applications as dental scaffolds. For this purpose, the mass loss, pH, glass transition temperature (Tg) and absorbed water mass of the different biopolymers have been obtained from samples into a phosphate-buffered saline solution (PBS) with initial pH of 7.

Dynamic rheological comparison of silicones for podiatry applications.

Purpose: This work shows an effective methodology to evaluate the dynamic viscoelastic behavior of silicones for application in podiatry. The aim is to characterize, compare their viscoelastic properties according to the dynamic stresses they can be presumably subjected when used in podiatry orthotic applications. These results provide a deeper insight which extends the previous creep-recovery results to the world of dynamic stresses developed in physical activity.

Statistical Modeling Applied to Deformation-Relaxation Processes in a Composite Biopolymer Network Induced by Magnetic Field.

This study investigated a methodology based on image processing and statistics to characterize and model the deformation upon controlled and uniform magnetic field and the relaxation under zero field of droplets observed in aqueous solutions of sodium alginate incorporating magnetic maghemite nanoparticles stabilized by adsorption of citrate ions. The changes of droplet geometry were statistically analyzed using a new approach based on the data obtained from optical microscopy, image processing, nonlinear regression, evolutionary optimization, analysis of variance and resampling. Image enhancement and then image segmentation (Gaussian mixture modeling) processes were applied to extract features with reliable information of droplets dimensions from optical micrographs.

Creep analysis of silicone for podiatry applications.

Purpose: This work shows an effective methodology to characterize the creep-recovery behavior of silicones before their application in podiatry. The aim is to characterize, model and compare the creep-recovery properties of different types of silicone used in podiatry orthotics.

Methods: Creep-recovery phenomena of silicones used in podiatry orthotics is characterized by dynamic mechanical analysis (DMA).