No abstract

No abstract

No abstract

In recent years, agriculture has become an essential activity in Colombia, despite the challenges faced by farmers due to low yields and insufficient resources to improve their main activities, such as irrigation systems, agricultural practices, and industrial machinery. This Hass avocado approach has been addressed in previous research considering system dynamics simulation to evaluate farmers’ behavior strategies and improve their competitiveness. However, these studies typically examine a single strategy effect and avoid multiple integrated strategies. Other studies focused on the complex interactions between different factors in the production chain and their feedback effects on farmers’ productivity and cash flow. For these reasons, this research provides a comprehensively dynamic model and evaluates long-term strategies and their effects on supporting and improving small farmers’ productivity and profitability. A system dynamics methodology was used to model complex systems processing Hass avocado farmer association data and explore their effects on competitiveness for long-term sustainable and profitable agriculture. This research proposes optimal scenarios for small farmers, including strategies such as low-interest credit access, logistics practices, and government technical support. The scenarios provide a proactive tool for decision makers and promote rural farmers’ development, aligning high-quality fresh product supply and demand.

El presente artículo de investigación propone un Modelo de Dinámica de Sistemas para la Gestión del Emprendimiento del Fondo Emprender, el cual se construyó mediante la caracterización de la cadena de valor del proceso, usando la herramienta SIPOC,(Suppliers,Inputs,Process,Outputs and Costumers). Para la definición del problema, en términos estructurales, también fue aplicada mediante una adaptación del Modelo Causal, con el fin de establecer las interdependencias sistémicas y los ciclos de retroalimentación, posibilitando la construcción del modelo a través de la herramienta VENSIM, (Ventana Systems Inc), que utilizó como base conceptual el Diagrama Forrester. De igual manera se realizó una calibración del mismo con datos reales, y se desarrollaron simulaciones que determinaron los principales atributos y permitieron la caracterización del Modelo de Emprendimiento del Fondo Emprender; la quiebra de las empresas, el tiempo dedicado por los asesores a la evaluación de los proyectos, y, en menor grado, el número de planes de negocios evaluados, toda vez que el paradigma propuesto permitió identificar tanto los puntos críticos como de apalancamiento de un modelo dinámico como es el del emprendimiento, convirtiéndose así en una herramienta importante para su gestión.

No abstract

ObjectiveTo describe the clinical and epidemiological characteristics of newborn infants with SARS-CoV-2 infection notified in the Colombian Public Health Surveillance System.DesignThis epidemiological descriptive analysis was conducted using the data of all cases of newborn infants with confirmed SARS-CoV-2 infection notified in the surveillance system. Absolute frequencies and central tendency measures were calculated and a bivariate analysis comparing variables of interest with symptomatic and asymptomatic disease was performed.SettingPopulation-based descriptive analysis.PatientsLaboratory-confirmed COVID-19 cases in newborn infants (aged ≤28 days of life) reported to the surveillance system from 1 March 2020 to 28 February 2021.Results879 newborns were identified, corresponding to 0.04% of all reported cases in the country. The mean age at diagnosis was 13 days (range 0–28 days), 55.1% were male and most (57.6%) were classified as symptomatic. Preterm birth and low birth weight were identified in 24.0% and 24.4% of the cases, respectively. Common symptoms were fever (58.3%), cough (48.3%) and respiratory distress (34.9%). A higher prevalence of symptomatic newborns was seen in individuals with low birth weight for gestational age (prevalence ratio (PR): 1.51, 95% CI: 1.44 to 1.59) and newborns with underlying conditions (PR: 1.33, 95% CI: 1.13 to 1.55).ConclusionsThere were a low proportion of confirmed COVID-19 cases in the newborn population. A substantial number of newborns were classified as symptomatic, having low birth weight and being preterm. Clinicians caring for COVID-19-infected newborns should be aware of population characteristics that potentially contribute to disease manifestations and severity.

Purpose: This work aims to evaluate demand forecasting models to determine if using exogenous factors and machine learning techniques helps improve performance compared to univariate statistical models, allowing manufacturing companies to manage demand better.Design/methodology/approach: We implemented a multivariate Auto-Regressive Moving Average with eXogenous input (ARMAX) statistical model and a Neural Network-ARMAX (NN-ARMAX) hybrid model for forecasting. Later, we compared both to a standard univariate statistical model to forecast the demand for electrical products in a Colombian manufacturing company.Findings: The outcomes demonstrated that the NN-ARMAX model outperformed the other two. Indeed, demand management improved with the reduction of overstock and out-of-stock products.Research limitations/implications: The findings and conclusions in this work are limited to Colombian manufacturing companies that sell electrical products to the construction industry. Moreover, the experts from the company that provided us with the data also selected the external factors based on their own experiences, i.e., we might have disregarded potential factors.Practical implications: This work suggests that a model using neural networks and including exogenous variables can improve demand forecasting accuracy, promoting this approach in manufacturing companies dealing with demand planning issues.Originality/value: The findings in this work demonstrate the convenience of using the proposed hybrid model to improve demand forecasting accuracy and thus provide a reliable basis for its implementation in supply chain planning for the electrical/construction sector in Colombian manufacturing companies.