FACTORES DE RIESGO ASOCIADOS A EVENTRACIÓN ABDOMINAL EN PACIENTES POST OPERADOS DEL CENTRO MÉDICO NAVAL “CIRUJANO MAYOR SANTIAGO TÁVARA” DURANTE EL PERIODO 2016 – 2021

Introducción: La eventración abdominal, también conocida como la hernia incisional, representa una complicación postoperatoria que puede afectar a pacientes sometidos a cirugía abdominal. Su presencia implica una reducción en la calidad de vida del paciente y aumenta la carga económica y asistencial en el sistema de salud. El presente trabajo tiene como objetivo investigar los factores de riesgo asociados a la eventración abdominal en pacientes post operados del Centro Médico Naval “Cirujano Mayor Santiago Távara” durante el periodo comprendido entre 2016 – 2021. Objetivos: Determinar los factores de riesgo asociados a eventración abdominal en pacientes post operados del Centro Médico Naval “Cirujano Mayor Santiago Távara” durante el periodo 2016-2021. Métodos: El diseño de estudio es de tipo observacional, retrospectivo de casos y controles a través de recolección de datos de historias clínicas. Resultados: se encontró asociación con las siguientes variables. Abordaje quirúrgico sin malla (OR=5,47;IC95% 1,89- 15,82;p=0,002), tamaño de herida quirúrgica grande (OR=8,02;IC95% 1,25- 51,42;p=0,028), sobrepeso y obesidad (OR=12,82;IC95% 4,45-36,99;p=0,028). Mayor posibilidad de presentar eventración abdominal Conclusión: los factores de riesgo relacionados con eventración abdominal incluyen el uso de una técnica quirúrgica sin malla, el tamaño de la herida quirúrgica grande y un índice de masa corporal en rango de sobrepeso u obesida

Calibration and comparison of different CFD approaches for airflow analysis in a glass greenhouse

CFD has been increasingly applied to greenhouses to optimise indoor environmental conditions for cultivation and management. Numerical simulations have proved fundamental for the enhancement of energy-efficient design criteria and management procedures. The objective of the study is the comparison between different computational approaches for the study of airflow patterns in a representative study case of a glass greenhouse, also through the calibration of the models and the validation of simulation results against experimental data. A three-span greenhouse of about 300 m2 located in Emilia-Romagna (Italy) has been considered as study case. Several analyses with the same boundary and initial conditions were performed using two codes, broadly used for research and design purposes. With both programs, 2D or 3D models have been used and, for every case, the grid convergence was verified by performing multiple steady state analyses with increasingly finer meshes. The results led to define the most suitable solutions to set up computational models for the simulation of airflow patterns inside a greenhouse. The study provided a preliminary outline of the differences due to the adoption of various computational approaches characterised by different levels of accuracy and complexity. The results indicate the advisability of further developing the research by carrying out deeper experimental insights necessary to quantify more in detail the validity and the reliability of the adopted analytical methodologies

ICT monitoring and mathematical modelling of dairy cows performances in hot climate conditions: a study case in Po valley (Italy)

Automatic Milking Systems (AMS) measure and record specific data about milk production and cow behaviour, providing farmers with useful real-time information for each animal. At the same time, indoor climatic conditions in terms of temperature and humidity within a dairy livestock barn represent a well-known crucial issue in farm building design and management, since these parameters can remarkably influence cows behaviour, milk yield and animal welfare.The goal of the study is to develop and test an innovative procedure for the comprehensive analysis of AMS-generated multi-variable time-series, with a focus on the analysis of the relationship between milk production and indoor climatic conditions. The specific purpose of the study is to develop and test a mathematical computer procedure using AMS-generated data and environmental parameters, designed to provide a forecasting model based on the integration of milking data and temperature and humidity levels surveyed from local sensor grids, designed to model milk production scenarios and, specifically, yield trends depending on the expected environmental conditions.For this purpose, a typical Italian farm with AMS has been adopted as a study case and internal climatic data of the barn have been analysed to understand the influence of high values of the Temperature Humidity Index (THI) on milk production in time. Then the correlation between yield variations and THI has been computed and characterized. Finally, external climatic data have been used to forecast the milk production in summertime. Once the model was validated, tests has led to predict milk yield with a relative error smaller than 2%.This study represents a step of a research aimed to define integrated systems for cow monitoring and to develop guidelines for the optimization of barn layouts

ICT monitoring and mathematical modelling of dairy cows performances in hot climate conditions: a study case in Po valley (Italy)

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3D numerical modelling of temperature and humidity index distribution in livestock structures: a cattle-barn case study

In dairy cattle farming, heat stress largely impairs production, health, and animal welfare. This study aims to develop a workflow and a numerical analysis procedure to provide a real-time 3D distribution of the temperature and humidity index (THI) in a generic cattle barn based on temperature and humidity monitored in sample points, besides characterising the relationship between indoor THI and outside weather conditions. This research was carried out with reference to the study case of a cattle barn. A model has been developed to define the indoor three-dimensional spatial distribution of the Temperature-Humidity Index of a cattle barn based on environmental measurements at different heights of the building. As a core of the model, the Discrete Sibson Interpolation method was used to render a point cloud representing the THI values in the non-sampled areas. The area between 1-2 meters was emphasised as the region of most significant interest to quantify the heat waves perceived by dairy cows. The model represents an effective tool to distinguish different areas of the animal-occupied zone characterised by different values of THI

Lesson learned in big data for dairy cattle: advanced analytics for heat stress detection

This report provides an overview of the strategies for data management and data analysis developed within the EU project EIT Food DairySust “Big data and advanced analytics for sustainable management of the dairy cattle sector”. The main ambition of this project is to improve sustainability and animal welfare, besides productivity, in dairy farming, through advanced data analytics for every level of stakeholders. Good data management, in terms of acquisition, processing, harmonization and imputation, is required for good modelling for early diagnosis and for the identification of optimal prevention strategies, particularly in fields where monitoring can collect very heterogeneous data, and for which agreed protocols have not yet been standardized. The project investigated the “ecosystem” of data and application strategies for sharing computer resources and information in a secure and organic manner. This research first developed an optimal computational ecosystem based on the integration and harmonization of heterogeneous data types. Classical and advanced modelling strategies were used and compared. The results are suitable to provide the stakeholders with improved decision-making process about animal welfare and sustainability of the production. This report focuses on the implementation of a numerical model for the assessment of the impact of heat stress on milk production and provides a feedback on it

Smart Dairy Farming: Innovative Solutions to Improve Herd Productivity

Among the most straining trends that farmers have to face there are: on one side, to guarantee welfare and adequate life conditions for animals and to reduce the environmental footprint, on the other side, to develop new strategies to improve farm management reducing costs. The current conditions and the expected developments of the dairy sector highlight a strong need for more efficient and sustainable farming systems. Studying heat stress, herd management and housing and animals\u2019 productive and reproductive performances is fundamental for the economic and environmental sustainability of the dairy chain. New and effective tools to cope with these challenges have been provided by Precision Livestock Farming (PLF), which is nowadays increasingly applied and makes possible to control quali-quantitative parameters related to production, health, behaviour, and real-time locomotion per animal. The research key challenge is to turn these data into knowledge to provide real-time support in farming optimisation. This research focuses specifically on different systems to collect, process and derive useful information from data on animal welfare and productivity. A multi-disciplinary approach has been adopted to generate a decision support system for farmers