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Background Triage is essential for optimising resource allocation in emergency care, particularly in low- and middle-income countries. Some triage tools, such as the Interagency Integrated Triage Tool (IITT), have been developed specifically for resource-limited settings, but their implementation and evaluation remain challenging due to shortages of staff, limited training opportunities, and infrastructure constraints. This study aimed to evaluate the impact of implementing a structured triage system adapted from the IITT on the identification of urgent/emergency cases and wait times compared with unstructured nursing assessment alone in a rural general hospital in Uganda. Methods A prospective quality improvement study was conducted in the outpatient department (OPD) of Dr Ambrosoli Memorial Hospital in Kalongo, Uganda. Data were collected on all patients attending the OPD for 7 consecutive days before and after IITT implementation. Outcomes included changes in emergency/urgent cases identification, proportion of undertriage/overtriage using hospital admission as the gold standard for assessing triage accuracy, OPD wait times and total OPD length of stay. Multivariable regression was used to adjust for confounders. Results A total of 304 patients in the pre-implementation period and 246 patients in the post-implementation period were included in the analysis. After implementation of the IITT, the proportion of emergency/urgent cases increased from 16.4% to 22.8%, but there was no significant association between IITT implementation and identification of emergency/urgent cases, overtriage and undertriage after adjustment for confounders. IITT implementation was associated with a 23-minute reduction in time to provider (95% CI -35.49 to -12.03, p  < 0.001) and a 35-minute reduction in total OPD length of stay (95% CI -57.41 to -12.76, p  = 0.002). Conclusions A structured triage system adapted from the IITT showed similar proportions of overtriage and undertriage compared with unstructured nursing assessment alone, but improved patient flow by significantly reducing wait times and length of stay in the OPD of a resource-limited rural hospital in Uganda. These findings suggest that structured triage can be feasibly implemented without additional resources in similar low-resource hospitals; however, further studies are needed to fully assess the impact of IITT in this and similar settings.

The 2019 Geomorphological Field Camp at San Domino Island (Tremiti Islands, Southern Adriatic Sea) is the result of geological and geomorphological field work activities carried out by a group of students attending the Geomorphological field mapping course of the Master's Degree in Geological Science and Technology (University of Chieti-Pescara). The main map (1:5000 scale) was obtained through an integrated approach that incorporates morphometric analysis, geological and geomorphological field mapping, and geomorphological profiles drawing. Activities were carried out by all students, divided into six working groups of three to four persons each. The field camp and field work activities made it possible to produce a detailed thematic map, as a scientific tool to depict the San Domino Island landscape, and to outline some geomorphological issues in terms of possible constraints to landscape evolution, geomorphological processes distribution, and natural hazard assessment.

Issue Title: LXI ANNUAL MEETING of the ITALIAN SOCIETY for VETERINARY SCIENCES (SISVET) Salsomaggiore Terme (Parma) 2007

AI-based coding agents are increasingly integrated into software development workflows, collaborating with developers to create pull requests (PRs). Despite their growing adoption, the role of human-agent collaboration in software testing remains poorly understood. This paper presents an empirical study of 6,582 human-agent PRs (HAPRs) and 3,122 human PRs (HPRs) from the AIDev dataset. We compare HAPRs and HPRs along three dimensions: (i) testing frequency and extent, (ii) types of testing-related changes (code-and-test co-evolution vs. test-focused), and (iii) testing quality, measured by test smells. Our findings reveal that, although the likelihood of including tests is comparable (42.9% for HAPRs vs. 40.0% for HPRs), HAPRs exhibit a larger extent of testing, nearly doubling the test-to-source line ratio found in HPRs. While test-focused task distributions are comparable, HAPRs are more likely to add new tests during co-evolution (OR=1.79), whereas HPRs prioritize modifying existing tests. Finally, although some test smell categories differ statistically, negligible effect sizes suggest no meaningful differences in quality. These insights provide the first characterization of how human-agent collaboration shapes testing practices.