Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data

[EN] The agricultural sector faces the challenge of ensuring food security without an excessive burden on the environment. Simulationmodels provide excellent instruments for researchers to gainmore insight into relevant processes and best agricultural practices and provide tools for planners for decision making support. The extent to which models are capable of reliable extrapolation and prediction is important for exploring new farming systems or assessing the impacts of future land and climate changes. A performance assessmentwas conducted by testing six detailed state-of-the-artmodels for simulation of nitrate leaching (ARMOSA, COUPMODEL, DAISY, EPIC, SIMWASER/STOTRASIM, SWAP/ANIMO) for lysimeter data of the Wagna experimental field station in Eastern Austria, where the soil is highly vulnerable to nitrate leaching. Three consecutive phases were distinguished to gain insight in the predictive power of themodels: 1) a blind test for 2005 2008 in which only soil hydraulic characteristics, meteorological data and information about the agricultural management were accessible; 2) a calibration for the same period in which essential information on field observations was additionally available to the modellers; and 3) a validation for 2009 2011 with the corresponding type of data available as for the blind test. A set of statistical metrics (mean absolute error, root mean squared error, index of agreement,model efficiency, root relative squared error, Pearson's linear correlation coefficient) was applied for testing the results and comparing the models. None of the models performed good for all of the statistical metrics. Models designed for nitrate leaching in high-input farming systems had difficulties in accurately predicting leaching in low-input farming systems that are strongly influenced by the retention of nitrogen in catch crops and nitrogen fixation by legumes. An accurate calibration does not guarantee a good predictive power of the model. Nevertheless all models were able to identify years and crops with high- and low-leaching rates.This research was made possible by the GENESIS project of the EU 7th Framework Programme (Project No. 226536; FP7-ENV-2008-1). We are grateful for the experimental data provided by Joanneum Raum (Graz, Austria). The modelling team of Democritus University of Thrace would like to thank Per-Erik Jansson (Royal Institute of Technology, Stockholm, Sweden) for his valuable help during the application of Coup Model.Groenendijk, P.; Heinen, M.; Klammler, G.; Fank, J.; Kupfersberger, H.; Pisinaras, V.; Gemitzi, A.... (2014). Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data. Science of the Total Environment. 499:463-480. https://doi.org/10.1016/j.scitotenv.2014.07.002S46348049

Concatenantur sibi epistulae nostrae. Reading Ancient Latin Letter Collections

Il volume presenta gli esiti del Convegno Internazionale “Concatenantur sibi epistulae nostrae. Reading Ancient Latin Letter Collections” (23-24 settembre 2021). Filo conduttore è l’analisi dei criteri organizzativi negli epistolari latini composti tra l’età di Cicerone e la Tarda Antichità. I contributi mostrano come la volontà di creare una logica narrativa attraverso la disposizione delle lettere caratterizzi l’epistolografia latina sin dalle sue origini, fornendo così nuovi elementi per la comprensione del genere epistolare e delle sue caratteristiche

Altered fractionation short-course radiotherapy for stage II-III rectal cancer: A retrospective study

Purpose: To report the long-term outcomes of neoadjuvant altered fractionation short-course radiotherapy in 271 consecutive patients with stage II-III rectal cancer. Patients and Methods: This was a retrospective single institution study with median follow-up of 101 months (8.4 years). Patients who were alive at the time of analysis in 2018 were contacted to obtain functional outcome data (phone interview). Radiotherapy consisted of 25 Gy in 10 fractions of 2.5 Gy administered twice daily. Median time interval to surgery was 5 days. Results: Local relapse was observed in 12 patients (4.4%) after a median of 28 months. Overall survival after 5 and 10 years was 73 and 55.5%, respectively (corresponding disease-free survival 65.5 and 51%). Of all patients without permanent stoma, 79% reported no low anterior resection syndrome (LARS; 0–20 points), 9% reported LARS with 21–29 points and 12% serious LARS (30–42 points). Conclusion: The present radiotherapy regimen was feasible and resulted in low rates of local relapse. Most patients reported good functional outcomes

Pathologist computer-aided diagnostic scoring of tumor cell fraction: A Swiss national study.

Tumor cell fraction (TCF) estimation is a common clinical task with well-established large inter-observer variability. It thus provides an ideal testbed to evaluate potential impacts of employing a computer-aided diagnostic (TCFCAD) tool to support pathologists' evaluation. During a National Slide Seminar event, pathologists (n=69) were asked to visually estimate TCF in 10 regions of interest (ROI) from hematoxylin and eosin (H&E) colorectal cancer images intentionally curated for diverse tissue compositions, cellularity, and stain intensities. Next, they re-evaluated the same ROIs while being provided a TCFCAD created overlay highlighting predicted tumor versus non-tumor cells, together with the corresponding TCF percentage. Participants also reported confidence levels in their assessments using a 5-tiers scale, indicating no confidence to high confidence, respectively. The TCF ground truth (GT) was defined by manual cell-counting by experts. When assisted, inter-observer variability significantly decreased, showing estimates converging to the GT. This improvement remained even when TCFCAD predictions deviated slightly from the GT. The standard-deviation of estimated TCF to the GT across ROIs was 9.9% vs 5.8% with TCFCAD, p < 0.0001. The intraclass correlation coefficient increased from 0.8 to 0.93 (CI95% [0.65, 0.93] vs [0.86, 0.98]) and pathologists stated feeling more confident when aided (3.67 ± 0.81 vs. 4.17 ± 0.82 with CAD). TCFCAD estimation support demonstrated improved scoring accuracy, inter-pathologist agreement and scoring confidence. Interestingly, pathologists also expressed more willingness to use such a CAD tool at the end of the survey, highlighting the importance of training/education to increase adoption of CAD systems