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Abstract Veterinary guidelines have been published in the Netherlands to promote antimicrobial stewardship. An evidence-based intervention program using Implementation Mapping and performance indicators was developed to enhance veterinarians’ adherence to the veterinary guideline “Streptococcus suis in weaned pigs”. The present study evaluates the effect of this eight-month intervention program in a multicenter, pragmatic, stepped-wedge cluster design trial. Of the 49 veterinarians that participated, 33 provided data from 125 S. suis problem farms. A baseline measurement (M0) before the intervention program, and two measurements during (M1) and partly after (M2) the intervention program were conducted. A significant reduction in farm-level antimicrobial use of 25% in M1 and 49% in M2 was achieved compared to M0. For the performance indicators at veterinarian level, a significant reduction (− 36%) was found for antimicrobial prescription in M2, a significant increase occurred in argumentation for 2nd choice antimicrobials (M2) and the usage of bacteriological examination (M1). Two other performance indicators (ratio of 1st to 2nd or 3rd choice antimicrobials and corticosteroids) did not change significantly. These results show how an evidence-based intervention program to foster adherence to an existing veterinary clinical practice guideline achieved a significant reduction in antimicrobial prescriptions by swine veterinarians.

The fourth industrial revolution (Industry 4.0) brought significant changes in manufacturing, driven by technologies like artificial intelligence (AI), Internet of Things (IoT), 5G, robotics, and big data analytics. For industries to remain competitive, the primary goals must be the improvement of the efficiency and safety of machinery, the reduction of production costs, and the enhancement of product quality. Predictive maintenance (PdM) utilizes historical data and AI models to diagnose equipment’s health and predict the remaining useful life (RUL), providing critical insights for machinery effectiveness and product manufacturing. This prediction is a critical strategy to maximize the useful life of equipment, especially in large-scale and important infostructures. This study focuses on developing an unsupervised machine state-classification solution utilizing real-world industrial measurements collected from a pneumatic pressing machine. Unsupervised machine learning (ML) models were tested to diagnose and output the working state of the pressing machine at each given point (offline, idle, pressing, defective). Our research contributes to extracting valuable insights regarding real-world industrial settings for PdM and production efficiency using unsupervised ML, promoting operation safety, cost reduction, and productivity enhancement in modern industries.

Background: After years of significant decline, the incidence of Salmonella enterica serotype Enteritidis (SE) human infections in Europe has started stagnating in recent years. The reasons for this stagnation remain largely unclear and are possibly multifactorial and interconnected in nature. We assessed and ranked several potential determinants of the stagnating SE trend in Europe, as well as different options for intervention at the level of poultry health and production, public health (infra)structure, and pathogen biology. Methods: A Multi-Criteria Decision-Analysis (MCDA) approach based on the Analytical Hierarchy Process was used. Through two separate surveys, a European panel of Salmonella experts first provided weights for several pre-defined criteria and subsequently scored different potential determinants and options for intervention (i.e. alternatives) against the criteria, during 2020–21. The weighting and scoring were based on Saaty's pairwise comparisons. The final ranking of the alternatives was derived from the summation of the products of each criterion weight with the score of the corresponding alternative. Sensitivity analyses were performed to assess the impact of different methodological choices, including European regions, and domains of expertise on the ranking of the determinants and options for intervention. Results: The first and second-ranked determinants of the stagnated trend in human SE infections were related to poultry health and production, namely “inadequacies of sampling programmes” and “premature relaxation of control measures”. This ranking agreed with the ranking of the options for intervention, which were also those at the poultry health and production level, specifically “stricter biosecurity”, “improving sampling”, and “better/increased vaccination”. Differences in rankings were observed among European regions and domains of expertise. Conclusions: The rankings of potential determinants and options for intervention for the stagnating SE trend in Europe pointed to the level of poultry health and production. Salmonella-control activities in poultry in Europe are harmonized across countries since many years, but the results of this study suggest that further improvements may be necessary for some countries. A multidisciplinary collaboration among veterinarians, public health professionals, and microbiologists is needed to further understand the origins of the stagnating SE trend and to identify effective interventions in order to reverse the trend, contextually in a given country, following a One Health approach.