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21 results on '"Mallioris, Panagiotis"'

1. Development of a Decision Support System in a Canning Industry

Author

Mallioris, Panagiotis, Kokkas, Georgios, Styliadis-Heinz, Alexandros, Margaritis, Ioannis, Stergiopoulos, Fotios, Bechtsis, Dimitrios, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, and Arai, Kohei, editor

Published
2024
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9. Risk factors for antimicrobial use in Dutch pig farms: A cross-sectional study

Author

IRAS OH Epidemiology Chemical Agents, IRAS – One Health Chemical, Klinische infectiologie en microb. lab., Infectious Diseases and Immunology - KLIF, FAH – Sustainable Poultry & Porcine Health, FAH GZ varken, FAH veterinaire epidemiologie, FAH – One Health Epidemiology, IRAS – One Health Microbial, IRAS OH Epidemiology Microbial Agents, Mallioris, Panagiotis, Luiken, Roosmarijn E C, Tobias, Tijs, Vonk, John, Wagenaar, Jaap A, Stegeman, Arjan, Mughini-Gras, Lapo, IRAS OH Epidemiology Chemical Agents, IRAS – One Health Chemical, Klinische infectiologie en microb. lab., Infectious Diseases and Immunology - KLIF, FAH – Sustainable Poultry & Porcine Health, FAH GZ varken, FAH veterinaire epidemiologie, FAH – One Health Epidemiology, IRAS – One Health Microbial, IRAS OH Epidemiology Microbial Agents, Mallioris, Panagiotis, Luiken, Roosmarijn E C, Tobias, Tijs, Vonk, John, Wagenaar, Jaap A, Stegeman, Arjan, and Mughini-Gras, Lapo

Published
2024

12. Biosecurity and antimicrobial use in broiler farms across nine European countries: Toward identifying farm-specific options for reducing antimicrobial usage

Author

Mallioris, Panagiotis, Teunis, Gijs, Lagerweij, Giske, Joosten, Philip, Dewulf, Jeroen, Wagenaar, Jaap A, Stegeman, Arjan, Mughini-Gras, Lapo, EFFORT consortium, Mallioris, Panagiotis, Teunis, Gijs, Lagerweij, Giske, Joosten, Philip, Dewulf, Jeroen, Wagenaar, Jaap A, Stegeman, Arjan, Mughini-Gras, Lapo, and EFFORT consortium

Abstract

Broiler chickens are among the main livestock sectors worldwide. With individual treatments being inapplicable, contrary to many other animal species, the need for antimicrobial use (AMU) is relatively high. AMU in animals is known to drive the emergence and spread of antimicrobial resistance (AMR). High farm biosecurity is a cornerstone for animal health and welfare, as well as food safety, as it protects animals from the introduction and spread of pathogens and therefore the need for AMU. The goal of this study was to identify the main biosecurity practices associated with AMU in broiler farms and to develop a statistical model that produces customised recommendations as to which biosecurity measures could be implemented on a farm to reduce its AMU, including a cost-effectiveness analysis of the recommended measures. AMU and biosecurity data were obtained cross-sectionally in 2014 from 181 broiler farms across nine European countries (Belgium, Bulgaria, Denmark, France, Germany, Italy, the Netherlands, Poland and Spain). Using mixed-effects random forest analysis (Mix-RF), recursive feature elimination was implemented to determine the biosecurity measures that best predicted AMU at the farm level. Subsequently, an algorithm was developed to generate AMU reduction scenarios based on the implementation of these measures. In the final Mix-RF model, 21 factors were present: 10 about internal biosecurity, 8 about external biosecurity and 3 about farm size and productivity, with the latter showing the largest (Gini) importance. Other AMU predictors, in order of importance, were the number of depopulation steps, compliance with a vaccination protocol for non-officially controlled diseases, and requiring visitors to check in before entering the farm. K-means clustering on the proximity matrix of the final Mix-RF model revealed that several measures interacted with each other, indicating that high AMU levels can arise for various reasons depending on the situation. The alg

Published
2023

13. Assessing potential determinants of the stagnating trend in Salmonella Enteritidis human infections in Europe and options for intervention: A multi-criteria decision analysis.

Author

Klinische infectiologie en microb. lab., Infectious Diseases and Immunology - KLIF, IRAS OH Epidemiology Microbial Agents, IRAS – One Health Microbial, Chanamé Pinedo, Linda, Van Goethem, Nina, Mallioris, Panagiotis, Pacholewicz, Ewa, Pijnacker, Roan, Franz, Eelco, Mughini-Gras, Lapo, Klinische infectiologie en microb. lab., Infectious Diseases and Immunology - KLIF, IRAS OH Epidemiology Microbial Agents, IRAS – One Health Microbial, Chanamé Pinedo, Linda, Van Goethem, Nina, Mallioris, Panagiotis, Pacholewicz, Ewa, Pijnacker, Roan, Franz, Eelco, and Mughini-Gras, Lapo

Published
2023

14. Biosecurity and antimicrobial use in broiler farms across nine European countries: Toward identifying farm-specific options for reducing antimicrobial usage

Author

Klinische infectiologie en microb. lab., IRAS OH Epidemiology Chemical Agents, FAH veterinaire epidemiologie, IRAS OH Epidemiology Microbial Agents, FAH – One Health Epidemiology, IRAS – One Health Chemical, IRAS – One Health Microbial, Infectious Diseases and Immunology - KLIF, Mallioris, Panagiotis, Teunis, Gijs, Lagerweij, Giske, Joosten, Philip, Dewulf, Jeroen, Wagenaar, Jaap A, Stegeman, Arjan, Mughini-Gras, Lapo, EFFORT consortium, Klinische infectiologie en microb. lab., IRAS OH Epidemiology Chemical Agents, FAH veterinaire epidemiologie, IRAS OH Epidemiology Microbial Agents, FAH – One Health Epidemiology, IRAS – One Health Chemical, IRAS – One Health Microbial, Infectious Diseases and Immunology - KLIF, Mallioris, Panagiotis, Teunis, Gijs, Lagerweij, Giske, Joosten, Philip, Dewulf, Jeroen, Wagenaar, Jaap A, Stegeman, Arjan, Mughini-Gras, Lapo, and EFFORT consortium

Published
2023

15. Intelligent Quality Control in Cold Supply Chains.

Author

Mallioris, Panagiotis, Bechtsis, Dimitrios, Vlachos, Dimitrios, Papapanagiotakis, Georgios, Todi, Theodora, Papaspyropoulou, Maria, Georgakidis, Konstantinos, and Sfitis, Nikolaos

Subjects
SUPPLY chain management, MANUFACTURING processes, TOTAL quality management, ARTIFICIAL neural networks, QUALITY control
Abstract

Towards a sustainable and resilient digital cold supply chain, environment sensing technologies and Big data analytics combined with Artificial Intelligence can extract critical information and provide a systematic framework for product optimization and safety enhancement. Our research focuses on a descriptive analysis framework of a real-world dairy food distribution system, using historical data collected from embedded sensors inside refrigerated trucks. The dataset consists of 5,972 records that present the distribution schedule, the collected temperatures and the refrigerator’s open door window in seconds. The measurements are taken both on-route and while loading/unloading from various vehicles for two periods one in the winter and one in the summer. A Big data analysis approach combining statistical analysis and heterogenous data manipulation was conducted to extract critical results regarding truck refrigeration efficiency and dairy products safety zone. Additionally, Pearson analysis was performed to evaluate the correlation between temperature differences and the open-door condition. The results indicated that in the summer period, temperature fluctuations are intensified both on-route and at the delivery point compared with the winter period, and the operating time of the refrigerator is extended. Moreover, refrigeration performance differentiated amongst the vehicles due to the truck’s thermal characteristics i.e. inappropriate thermal insulation or even the human factor. The contribution of this research is to conduct a descriptive analysis of critical measurements comparing system characteristics between the summer and winter periods and to propose an effective analytical framework for optimizing the efficiency of the overall system in a real-world distribution use case. [ABSTRACT FROM AUTHOR]

Published
2023

16. Biosecurity and antimicrobial use in broiler farms across nine European countries: towards identifying farm-specific options for reducing antimicrobial usage

Author

Mallioris, Panagiotis, Teunis, Gijs, Lagerweij, Giske, Joosten, Philip, Dewulf, Jeroen, Wagenaar, Jaap A., Stegeman, Arjan, Mughini-Gras, Lapo, and EFFORT Consortium, [missing]

Subjects
FOOD-PRODUCING ANIMALS, broilers, Epidemiology, mixed-effects random, antimicrobial use, forest, Infectious Diseases, Antibiotics, HISTORY, CAMPYLOBACTER SPP, RISK-FACTORS, Veterinary Sciences, RESISTANCE, random forest, biosecurity
Abstract

Broiler chickens are among the main livestock sectors worldwide. With individual treatments being inapplicable, contrary to many other animal species, the need for antimicrobial use (AMU) is relatively high. AMU in animals is known to drive the emergence and spread of antimicrobial resistance (AMR). High farm biosecurity is a cornerstone for animal health and welfare, as well as food safety, as it protects animals from the introduction and spread of pathogens and therefore the need for AMU. The goal of this study was to identify the main biosecurity practices associated with AMU in broiler farms and to develop a statistical model that produces customised recommendations as to which biosecurity measures could be implemented on a farm to reduce its AMU, including a cost-effectiveness analysis of the recommended measures. AMU and biosecurity data were obtained cross-sectionally in 2014 from 181 broiler farms across nine European countries (Belgium, Bulgaria, Denmark, France, Germany, Italy, the Netherlands, Poland and Spain). Using mixed-effects random forest analysis (Mix-RF), recursive feature elimination was implemented to determine the biosecurity measures that best predicted AMU at the farm level. Subsequently, an algorithm was developed to generate AMU reduction scenarios based on the implementation of these measures. In the final Mix-RF model, 21 factors were present: 10 about internal biosecurity, 8 about external biosecurity and 3 about farm size and productivity, with the latter showing the largest (Gini) importance. Other AMU predictors, in order of importance, were the number of depopulation steps, compliance with a vaccination protocol for non-officially controlled diseases, and requiring visitors to check in before entering the farm. K-means clustering on the proximity matrix of the final Mix-RF model revealed that several measures interacted with each other, indicating that high AMU levels can arise for various reasons depending on the situation. The algorithm utilised the AMU predictive power of biosecurity measures while accounting also for their interactions, representing a first step toward aiding the decision-making process of veterinarians and farmers who are in need of implementing on-farm biosecurity measures to reduce their AMU.

Published
2022

17. Factors associated with antimicrobial use in pig and veal calf farms in the Netherlands: A multi-method longitudinal data analysis

Author

Klinische infectiologie en microb. lab., dI&I I&I-4, IRAS OH Epidemiology Microbial Agents, dIRAS RA-I&I I&I, FAH veterinaire epidemiologie, dFAH AVR, dFAH I&I, Mallioris, Panagiotis, Dohmen, Wietske, Luiken, Roosmarijn E C, Wagenaar, Jaap A, Stegeman, Arjan, Mughini-Gras, Lapo, Klinische infectiologie en microb. lab., dI&I I&I-4, IRAS OH Epidemiology Microbial Agents, dIRAS RA-I&I I&I, FAH veterinaire epidemiologie, dFAH AVR, dFAH I&I, Mallioris, Panagiotis, Dohmen, Wietske, Luiken, Roosmarijn E C, Wagenaar, Jaap A, Stegeman, Arjan, and Mughini-Gras, Lapo

Published
2022

20. Modulation of intestinal health and hepatic vacuolation in gilthead sea bream (Sparus aurata) juveniles by a mixture of dietary esterified butyrins, emulsifiers from plants and yeast extracts at low and high fish meal inclusion

Author

Mallioris, Panagiotis, primary, Kotzamanis, Yannis, additional, Vardali, Sofia, additional, Roussos, Efstratios, additional, Ilia, Vasiliki, additional, Paschali, Elissavet, additional, Kampantais, Dimitrios, additional, Bouziotis, Dimitrios, additional, Khadem, Alireza, additional, and Vatsos, Ioannis N., additional

Published
2021
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21. High Accuracy Data Management and Processing Models

Author

Bechtsis Dimitrios, Vlachos Dimitrios, Mallioris Panagiotis, and Sidiropoulos Athanasios

Subjects
Computer science, business.industry, Data management, Data mining, business, computer.software_genre, computer
Published
2021

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