A framework for validating watershed ecosystem service models in the United States using long-term water quality data: Applications with the InVEST Nutrient Delivery (NDR) model in Puerto Rico.

Modeling of watershed Ecosystem Services (ES) processes has increased greatly in recent years, potentially improving environmental management and decision-making by describing the value of nature. ES models may be sensitive to different conditions and, therefore, should ideally be validated against observed data for their use as a decision-support instrument. However, outcomes from such ES modeling are barely validated, making it difficult to assess uncertainties associated with the modeling and justify their actual usefulness to develop generalizable management recommendations. This study proposes a framework for the systematic validation of one of such tools, the InVEST Nutrient Delivery Model (NDR) for nutrient retention estimates. The framework is divided into three stages: 1) running the NDR model inputs, processes, and outputs; 2) building a long-term reference dataset from open access water quality observations; and 3) using the reference data for model calibration and validation. We applied this framework to twenty watersheds in the Commonwealth of Puerto Rico, where data availability resembles thar of watersheds across the United States. Long-term water quality data from monitoring stations facilitated model calibration and validation. Our framework provided a reproducible method to linking the vast monitoring network in the U.S. and its territories for evaluating the InVEST's NDR model performance. Beyond the framework development, this study found that the InVEST NDR model explained 62.7 % and 79.3 % of the variance in the total nitrogen and total phosphorus between 2000 and 2022, respectively, supporting the suitability of the model for watershed scale ecosystem services assessment. The findings can also serve as a reference to support the use of InVEST for other locations in the tropics without publically available monitoring data.

Wood volume is overestimated in the Brazilian Amazon: Why not use generic volume prediction methods in tropical forest management?

The Amazon has a range of species with high potential for sustainable timber harvesting, but for them to be utilized globally, the merchantable wood volume must be accurately quantified. However, since the 1950s, inadequate methods for estimating merchantable timber volumes have been employed in the Amazon, and Brazilian Government agencies still require some of them. The natural variability of the Amazon Forest provides an abundance of species of different sizes and shapes, conferring several peculiarities, which makes it necessary to use up-to-date and precise methods for timber quantification in Amazon Forest management. Given the employment of insufficient estimation methods for wood volume, this study scrutinizes the disparities between the actual harvested merchantable wood volume and the volume estimated by the forest inventory during the harvesting phase across five distinct public forest areas operating under sustainable forest management concessions. We used mixed-effect models to evaluate the relationships between inventory and harvested volume for genera and forest regions. We performed an equivalence test to assess the similarity between the volumes obtained during the pre-and post-harvest phases. We calculated root mean square error and percentage bias for merchantable volume as accuracy metrics. There was a strong tendency for the 100% forest inventory to overestimate merchantable wood volume, regardless of genus and managed area. There was a significant discrepancy between the volumes inventoried and harvested in different regions intended for sustainable forest management, in which only 22% of the groups evaluated were equivalent. The methods currently practiced by forest companies for determining pre-harvest merchantable volume are inaccurate enough to support sustainable forest management in the Amazon. They may even facilitate the region's illegal timber extraction and organized crime.

Regional climate modeling in the Amazon basin to evaluate fire risk / Modelagem climática regional na bacia Amazônica para avaliação do risco de fogo

Studies regarding deforestation, the hydrological cycle, climate change and fire weather can benefit from the detailed simulations provided by regional climate models (RCM). While much attention has been given to fire activity in the Amazon, few studies have used RCM runs to assess fire risk and variables associated to fire occurrence. We evaluated precipitation, temperature and a fire risk index from the ensemble of Eta model simulations coupled with three different global climate models for the Amazon basin. The RCM runs were compared to reanalysis data for the dry season from 1979 to 2005. The maximum and 2-m temperature fields were underestimated over the entire region, but showed a statistically significant spatial correlation with the reference data. Precipitation was overestimated over the Amazon, in accordance with the major sources of moisture analyzed. The Keetch-Byram drought index (KBDI) was not significantly affected by the bias found in temperature and precipitation, and the ensemble improved relative to the individual member simulations. KBDI estimations performed better with the ensemble of the three evaluated members, however the Eta model showed some limitations. The validation of modeled fire risk could benefit from the use of satellite hotspot data. Furthermore, the KBDI can also be used in the assessment of how climate change interacts with fire activity in the Amazon region.(AU)

Estudos sobre desmatamento, ciclo hidrológico, mudanças climáticas e fogo podem se beneficiar de simulações mais detalhadas provenientes de modelos climáticos regionais (RCM). Apesar de que a atividade do fogo na Amazônia tenha recebido grande atenção, poucos estudos usaram simulações de RCM para avaliar o risco de fogo e variáveis associadas às condições climáticas favoráveis à ocorrência de fogo. Aqui avaliamos precipitação, temperatura e um índice de risco de fogo do conjunto de simulações do modelo Eta forçado para três modelos climáticos globais diferentes para a bacia Amazônica. As simulações de RCM foram comparadas com dados de reanálise para a estação seca de 1979 a 2005. Os campos de temperatura máxima e de 2 m foram subestimados em toda a região, porém mostraram uma correlação espacial estatisticamente significativa com os dados de referência. A precipitação foi superestimada para toda a Amazônia, em acordo com as principais fontes de umidade analisadas. O índice de seca de Keetch-Byram (KBDI) não foi significativamente afetado pelo viés observado na temperatura e na precipitação, e o conjunto apresentou resultados melhores em comparação com as simulações dos membros individuais. As simulações de KBDI tiveram melhor resultado com o conjunto das três variáveis avaliadas, porém o modelo Eta mostrou algumas limitações. A validação dos modelos de risco de fogo poderia se beneficiar do uso de dados de hotspot satelitais. Além disso, o KBDI pode ser usado na avaliação de como as mudanças climáticas interagem com o fogo na região amazônica.(AU)

Psychometric Properties of a Cyberaggression Measure in Mexican Students.

Cyberaggression is an important problem today; it can affect adolescents in different ways. Therefore, reliable and valid measures are necessary to better study the phenomenon. The aim of the present study was to generate validity and reliability evidence for a Spanish-language cyberaggression scale from Garaigordobil, (2017) in a population of 1695 adolescents from northwestern Mexico (51.5% female) between 12- and 15-years-of-age. The results of this study contribute to the research and focus on cyberaggression in adolescents in Mexico. The measure used in this paper detects the different roles, including the bystander, rigorously testing the reliability and validity of the measure, providing a solid tool to evaluate cyberaggression in the Mexican context and guide evidence-based interventions and policies in educational settings.

Modelo pedagógico para el mejoramiento del sistema de evaluación del residente de Ginecología y Obstetricia / Pedagogical model for improving the evaluation system of gynecology and obstetrics residents

Introducción: El proceso de evaluación en las especialidades médicas tiene su base en la valoración del desempeño para lograr una formación en respuesta al encargo social, lo que requiere de la preparación de los profesores para desarrollar las capacidades que les permitan llevar a cabo un proceso con este enfoque. Objetivo: Proponer un modelo pedagógico para el mejoramiento del sistema de evaluación del residente de Ginecología y Obstetricia en la Facultad de Ciencias Médicas Finlay-Albarrán, en correspondencia con las exigencias sociales y del Sistema Nacional de Salud cubano. Métodos: Se utilizaron métodos teóricos, empíricos y estadísticos, y otros como la parametrización y la triangulación metodológica. La participación de profesores, directivos y residentes del departamento docente de Ginecología y Obstetricia representó el 74,1 por ciento del universo estudiado. Resultados: Se propone un modelo pedagógico que se estructura en dos niveles: conceptual y metodológico. El conceptual comprende los fundamentos teóricos, las ideas científicas, las dimensiones y la finalidad. El metodológico se concreta en su dinámica de aplicación y se organiza en cuatro etapas con objetivos y acciones definidas. Los fundamentos, relacionados entre sí, posibilitaron la organización de las acciones dirigidas para su estructuración. La triangulación metodológica de los resultados de su evaluación valoró positivamente la viabilidad teórica del modelo pedagógico que se presenta. Conclusiones: La modelación como método científico permitió la elaboración de un modelo pedagógico para el mejoramiento del sistema de evaluación del residente de Ginecología y Obstetricia en la Facultad de Ciencias Médicas Finlay-Albarrán. Los resultados obtenidos permitieron declarar su validez teórica(AU)

Introduction: The evaluation process in medical specialties is based on performance evaluation to achieve training in response to the social order, which requires the preparation of teachers to develop the capacities which allow them to carry out a process by this approach. Objective: To propose a pedagogical model for the improvement of the evaluation system of gynecology and obstetrics residents at Finlay-Albarrán Medical Sciences Faculty, in correspondence with the social demands and the Cuban National Health System. Methods: Theoretical, empirical and statistical methods were used, as well as parameterization and methodological triangulation. The participation of professors, directors and residents of gynecology and obstetrics teaching department represented 74.1 percent of the studied universe. Results: A two-level structured pedagogical model is proposed: conceptual and methodological levels. The conceptual level comprises the theoretical foundations, scientific ideas, dimensions and purpose. The methodological level is itemized in application dynamics and it is organized in four stages with defined objectives and actions. The interrelated foundations made possible the organization of actions engaged for structuring. The methodological triangulation of the results of its evaluation positively valued the theoretical viability of the pedagogical model that is presented. Conclusions: Modeling as a scientific method allowed elaborating a pedagogical model for improving the evaluation system of the gynecology and obstetrics resident at Finlay-Albarrán Medical Sciences Faculty. The results obtained allowed to declare its theoretical validity(AU)

Dataset on water-glycerol flow in a horizontal pipeline with and without leaks.

The dataset presented in this article was collected in a laboratory flow circuit, which was designed to investigate high-viscosity flows. The data set is composed of 1200 s (equivalent to 12,000 samples) of mass flow and pressure measurements taken at five points along the pipeline. The first 300 s were recorded when the flow in the loop was composed only of glycerol. The remaining data were acquired when the flow was composed of a water-glycerol mixture. During the data acquisition, two extractions were produced. The research reported in [1] uses 160 s of the data provided here. This article explains in detail the experimental set-up and the principal instruments used for obtaining the dataset. The dataset is in the form of seven columns: Time, Mass Flow, Pressure 1, Pressure 2, Pressure 3, Pressure 4, Pressure 5, in supplementary Excel and Matlab files.

Theoretical framework for the estimation of H2S concentration in biogas produced from complex sulfur-rich substrates.

A theoretical framework was developed and validated for the estimation of H2S concentration in biogas produced from complex sulfur-rich effluents. The modeling approach was based on easy-to-obtain data such as biological biogas potential (BBP), chemical oxygen demand, and total sulfur content. Considering the few data required, the model fitted well the experimental H2S concentrations obtained from BBP tests and continuous bioreactors reported in the literature. The model supported a correlation coefficient (R2) of 0.989 over the experimental data, obtaining average and maximum errors of ~ 25 and ~ 35%, respectively. The theoretical framework yielded good estimations for a wide range of experimental H2S concentrations (0.2 to 4.5% in biogas). This modeling approach is, therefore, a useful tool towards anticipating the H2S concentration in biogas produced from sulfur-rich substrates and deciding whether the installation of a desulfurization technology is required or not.

Virtual Screening Techniques in Drug Discovery: Review and Recent Applications.

The discovery of bioactive molecules is an expensive and time-consuming process and new strategies are continuously searched for in order to optimize this process. Virtual Screening (VS) is one of the recent strategies that has been explored for the identification of candidate bioactive molecules. The number of new techniques and software that can be applied in this strategy has grown considerably in recent years, so, before their use, it is necessary to understand the basics an also the limitations behind each one to get the most out of them. It is also necessary to assess the real contributions of this strategy so that more significant progress can be made in the future. In this context, this review aims to discuss some important points related to VS, including the use of virtual ligand and biotarget libraries, structurebased and ligand-based VS techniques, as well as to present recent cases where this strategy was successfully applied.

Managing household socio-hydrological risk in Mexico city: A game to communicate and validate computational modeling with stakeholders.

Residents of Mexico City experience major hydrological risks, including flooding events and insufficient potable water access for many households. A participatory modeling project, MEGADAPT, examines hydrological risk as co-constructed by both biophysical and social factors and aims to explore alternative scenarios of governance. Within the model, neighborhoods are represented as agents that take actions to reduce their sensitivity to exposure and risk. These risk management actions (to protect their households against flooding and scarcity) are based upon insights derived from focus group discussions within various neighborhoods. We developed a role-playing game based on the model's rules in order to validate the assumptions we made about residents' decision-making given that we had translated qualitative information from focus group sessions into a quantitative model algorithm. This enables us to qualitatively validate the perspective and experience of residents in an agent-based model mid-way through the modeling process. Within the context of described hydrological events and the causes of these events, residents took on the role of themselves in the game and were asked to make decisions about how to protect their households against scarcity and flooding. After the game, we facilitated a discussion with residents about whether or not the game was realistic and how it could be improved. The game helped to validate our assumptions, validate the model with community members, and reinforced our connection with the community. We then discuss the potential further development of the game as a learning and communication tool.

Validation of kinetic modeling of progesterone release from polymeric membranes.

Mathematical modeling in drug release systems is fundamental in development and optimization of these systems, since it allows to predict drug release rates and to elucidate the physical transport mechanisms involved. In this paper we validate a novel mathematical model that describes progesterone (Prg) controlled release from poly-3-hydroxybutyric acid (PHB) membranes. A statistical analysis was conducted to compare the fitting of our model with six different models and the Akaike information criterion (AIC) was used to find the equation with best-fit. A simple relation between mass and drug released rate was found, which allows predicting the effect of Prg loads on the release behavior. Our proposed model was the one with minimum AIC value, and therefore it was the one that statistically fitted better the experimental data obtained for all the Prg loads tested. Furthermore, the initial release rate was calculated and therefore, the interface mass transfer coefficient estimated and the equilibrium distribution constant of Prg between the PHB and the release medium was also determined. The results lead us to conclude that our proposed model is the one which best fits the experimental data and can be successfully used to describe Prg drug release in PHB membranes.

Leaf area estimation from linear measurements in different ages of Crotalaria juncea plants

ABSTRACT The goal of this study was to estimate the leaf area of Crotalaria juncea according to the linear dimensions of leaves from different ages. Two experiments were conducted with C. juncea cultivar IAC-KR1, in the 2014/2015 sowing seasons. At 59, 82, 102, 129 days after sowing (DAS) of the first and 61, 80, 92, 104 DAS of the second experiment, 500 leaves were collected, totaling 4,000 leaves. In each leaf, the linear dimensions were measured (length, width, length/width ratio and length × width product) and the specific leaf area was determined through Digimizer and Sigma Scan Pro software, after scanning images. Then, 3,200 leaves were randomly separated to generate mathematical models of leaf area (Y) in function of linear dimension (x), and 800 leaves for the models validation. In C. juncea, the leaf areas determined by Digimizer and Sigma Scan Pro software are identical. The estimation models of leaf area as a function of length × width product showed superior adjustments to those obtained based on the evaluation of only one linear dimension. The linear model Ŷ=0.7390x (R2=0.9849) of the real leaf area (Y) as a function of length × width product (x) is adequate to estimate the C. juncea leaf area.

MODELO DE EDUCACIÓN AMBIENTAL NO FORMAL PARA LA PROTECCIÓN DE LOS HUMEDALES BAÑÓ Y LOS NEGROS / NON-FORMAL ENVIRONMENTAL EDUCATION MODEL FOR THE PROTECTION OF THE BAÑÓ AND LOS NEGROS WETLANDS

El propósito de este artículo fue generar y validar un modelo de educación ambiental no formal para la conservación con fines de protección de los humedales Bañó y Los Negros, ubicados en el bajo Sinú, entre los corregimientos de Cotocá Arriba, Castilleral y Palo de Agua, pertenecientes al área rural del municipio de Lorica, departamento de Córdoba, Colombia. Para ello, se definieron una serie de elementos constitutivos del modelo, entre éstos se señala el perfil ambiental del territorio obtenido a partir de un diagnóstico de la zona de estudio, la identificación de los factores que inciden en conductas negativas por parte de los habitantes de los humedales hacia este tipo de ecosistemas, además de la definición de una base pedagógica, partiendo de los elementos antes mencionados. Con base en la integración de los elementos se determinó el cuarto componente del modelo, es decir, los enfoques bajo los cuales se desarrollaría éste: sistémico, de desarrollo sostenible, interdisciplinario y comunitario; se buscó generar un modelo desde una visión holística, en la cual la comunidad fuera un actor fundamental en su implementación y contribuyera al desarrollo sostenible de los humedales, teniendo en cuenta la interdisciplinariedad como componente integrador. La materialización del modelo o su fase de validación se concretó en un programa educativo piloto de corte no formal que contó con una población beneficiada, metas y objetivos bien definidos, así como la identificación de los problemas a intervenir a partir del diagnóstico del territorio. Se estableció que los contenidos programáticos, metodología y herramientas pedagógicas dependerían de la definición de los componentes arriba indicados. Se propuso como un mecanismo de evaluación para el modelo y el programa piloto, derivado del mismo, la aplicación del ciclo PHVA (planear, hacer, verificar y actuar).

The main purpose of this article is to generate and to validate a non-formal environmental education model for the conservation and protection of the Bañó and Los Negros wetlands, located in the lower Sinú region, between the districts of Cotocá Arriba, Castilleral and Palo de Agua, within the rural areas of the municipality of Lorica, in the Department of Córdoba, Colombia. For this purpose, a series of constitutive elements of the model were defined including the environmental profile of the territory obtained from a diagnosis of the area of study, the factors impinging on negative behavior on the part of the wetlands inhabitants towards those types of ecosystems were defined, besides the definition of a pedagogical basis was drawn from the above mentioned elements. Based on the integration of those elements, the fourth component of the model was identified, this is to say, the approaches under which it would be developed were obtained: systemic, sustainable, interdisciplinary and community developed. A model was searched from a comprehensive vision in which the community was a fundamental actor in its implementation and contributed to the sustainable development of the wetlands considering interdisciplinarity as an integrating component. The materialization of the model or its validation phase was specified through a non-formal educational pilot program that counted with a benefited population, well defined goals and objectives, as well as the identification of the problems to be intervened, drawn from the diagnosis of the territory. It was established that the contents, methodology and pedagogic tools would depended upon the definition of the above-mentioned components. The PDCA (planning, doing, checking and acting) cycle was proposed as a mechanism for evaluating the model and the pilot program derived from it.

Reliability of Degree-Day Models to Predict the Development Time of Plutella xylostella (L.) under Field Conditions.

The diamondback moth, Plutella xylostella (L.), is a cosmopolitan pest of brassicaceous crops occurring in regions with highly distinct climate conditions. Several studies have investigated the relationship between temperature and P. xylostella development rate, providing degree-day models for populations from different geographical regions. However, there are no data available to date to demonstrate the suitability of such models to make reliable projections on the development time for this species in field conditions. In the present study, 19 models available in the literature were tested regarding their ability to accurately predict the development time of two cohorts of P. xylostella under field conditions. Only 11 out of the 19 models tested accurately predicted the development time for the first cohort of P. xylostella, but only seven for the second cohort. Five models correctly predicted the development time for both cohorts evaluated. Our data demonstrate that the accuracy of the models available for P. xylostella varies widely and therefore should be used with caution for pest management purposes.

On the predictive ability of mechanistic models for the Haitian cholera epidemic.

Predictive models of epidemic cholera need to resolve at suitable aggregation levels spatial data pertaining to local communities, epidemiological records, hydrologic drivers, waterways, patterns of human mobility and proxies of exposure rates. We address the above issue in a formal model comparison framework and provide a quantitative assessment of the explanatory and predictive abilities of various model settings with different spatial aggregation levels and coupling mechanisms. Reference is made to records of the recent Haiti cholera epidemics. Our intensive computations and objective model comparisons show that spatially explicit models accounting for spatial connections have better explanatory power than spatially disconnected ones for short-to-intermediate calibration windows, while parsimonious, spatially disconnected models perform better with long training sets. On average, spatially connected models show better predictive ability than disconnected ones. We suggest limits and validity of the various approaches and discuss the pathway towards the development of case-specific predictive tools in the context of emergency management.

Pantograph: A template-based method for genome-scale metabolic model reconstruction.

Genome-scale metabolic models are a powerful tool to study the inner workings of biological systems and to guide applications. The advent of cheap sequencing has brought the opportunity to create metabolic maps of biotechnologically interesting organisms. While this drives the development of new methods and automatic tools, network reconstruction remains a time-consuming process where extensive manual curation is required. This curation introduces specific knowledge about the modeled organism, either explicitly in the form of molecular processes, or indirectly in the form of annotations of the model elements. Paradoxically, this knowledge is usually lost when reconstruction of a different organism is started. We introduce the Pantograph method for metabolic model reconstruction. This method combines a template reaction knowledge base, orthology mappings between two organisms, and experimental phenotypic evidence, to build a genome-scale metabolic model for a target organism. Our method infers implicit knowledge from annotations in the template, and rewrites these inferences to include them in the resulting model of the target organism. The generated model is well suited for manual curation. Scripts for evaluating the model with respect to experimental data are automatically generated, to aid curators in iterative improvement. We present an implementation of the Pantograph method, as a toolbox for genome-scale model reconstruction, curation and validation. This open source package can be obtained from: http://pathtastic.gforge.inria.fr.