Individual claims reserving using the Aalen--Johansen estimator

We propose an individual claims reserving model based on the conditional Aalen--Johansen estimator, as developed in Bladt and Furrer (2023b). In our approach, we formulate a multi-state problem, where the underlying variable is the individual claim size, rather than time. The states in this model represent development periods, and we estimate the cumulative density function of individual claim costs using the conditional Aalen--Johansen method as transition probabilities to an absorbing state. Our methodology reinterprets the concept of multi-state models and offers a strategy for modeling the complete curve of individual claim costs. To illustrate our approach, we apply our model to both simulated and real datasets. Having access to the entire dataset enables us to support the use of our approach by comparing the predicted total final cost with the actual amount, as well as evaluating it in terms of the continuously ranked probability score, as discussed in Gneiting and A. E. Raftery (2007

GEMAct: a Python package for non-life (re)insurance modeling

This paper introduces $\textbf{gemact}$, a $\textbf{Python}$ package for actuarial modelling based on the collective risk model. The library supports applications to risk costing and risk transfer, loss aggregation, and loss reserving. We add new probability distributions to those available in $\textbf{scipy}$, including the (a, b, 0) and (a, b, 1) discrete distributions, copulas of the Archimedean family, the Gaussian, the Student t and the Fundamental copulas. We provide an implementation of the AEP algorithm for calculating the cumulative distribution function of the sum of dependent, non-negative random variables, given their dependency structure specified with a copula. The theoretical framework is introduced at the beginning of each section to give the reader with a sufficient understanding of the underlying actuarial models

Soil characterization for shallow landslides modeling: a case study in the Northern Apennines (Central Italy)

In this paper, we present preliminary results of the IPL project No. 198 \u201cMulti-scale rainfall triggering models for Early Warning of Landslides (MUSE).\u201d In particular, we perform an assessment of the geotechnical and hydrological parameters affecting the occurrence of landslides. The aim of this study is to improve the reliability of a physically based model high resolution slope stability simulator (HIRESSS) for the forecasting of shallow landslides. The model and the soil characterization have been tested in Northern Tuscany (Italy), along the Apennine chain, an area that is historically affected by shallow landslides. In this area, the main geotechnical and hydrological parameters controlling the shear strength and permeability of soils have been determined by in situ measurements integrated by laboratory analyses. Soil properties have been statistically characterized to provide more refined input data for the slope stability model. Finally, we have tested the ability of the model to predict the occurrence of shallow landslides in response to an intense meteoric precipitation

Replicating and extending chain-ladder via an age-period-cohort structure on the claim development in a run-off triangle

This paper introduces yet another stochastic model replicating chain-ladder estimates and furthermore considers extensions that add flexibility to the modeling. In its simplest form, the proposed model replicates the chain-ladder's development factors using a GLM model with averaged hazard rates running in reversed development time as response. This is in contrast to the existing reserving literature within the GLM framework where claim amounts are modeled as response. Modeling the averaged hazard rate corresponds to modeling the claim development and is arguably closer to the actual chain-ladder algorithm. Furthermore, since exposure does not need to be modeled, the model only has half the number of parameters compared to when modeling the claim amounts. This lesser complexity can be used to easily introduce model extensions that may better fit the data. We provide a new R-package, $\texttt{clmplus}$, where the models are implemented and can be fed with run-off triangles. We conduct an empirical study on 30 publicly available run-off triangles making a case for the benefit of having $\texttt{clmplus}$ in the actuary's toolbox

Individual fitness is decoupled from coarse‐scale probability of occurrence in North American trees

Habitat suitability estimated with probability of occurrence in species distribution models (SDMs) is used in conservation to identify geographic areas that are most likely to harbor individuals of interest. In theory, probability of occurrence is coupled with individual fitness so that individuals have higher fitness at the centre of their species environmental niche than at the edges, which we here define as 'fitness‐centre' hypothesis. However, such relationship is uncertain and has been rarely tested across multiple species. Here, we quantified the relationship between coarse‐scale probability of occurrence projected with SDMs and individual fitness in 66 tree species native of North America. We used 1) field data of individuals' growth rate (height and diameter standardized by age) available from the United States Forest Inventory Analysis plots; and 2) common garden data collected from 23 studies reporting individual growth rate, survival, height and diameter of individuals originated from different provenances in United States and Canada. We show 'fitness–centre' relationships are rare, with only 12% and 11% of cases showing a significant positive correlation for field and common garden data, respectively. Furthermore, we found the 'fitness–centre' relationship is not affected by the precision of the SDMs and it does not depend upon dispersal ability and climatic breath of the species. Thus, although the 'fitness–centre' relationship is supported by theory, it does not hold true in nearly any species. Because individual fitness plays a relevant role in buffering local extinction and range contraction following climatic changes and biotic invasions, our results encourage conservationists not to assume the 'fitness–centre' relationship when modelling species distribution

Can Shading Affect Nitrogen Fixation Of Forage Legume Swards? An Assessment Of B-Value Through The 15N Natural Abundance Method

Tree-based intercropping systems are gaining pace as a land-use strategy to cope with climate change and provide environmental, economic, and social benefits. The integration of nitrogen-fixing crops between trees can be a solution to increase the land productivity and reduce the reliance on external inputs by increasing nitrogen (N) availability and then both tree and crop growth. Intercropping perennial legumes with trees can also reduce nitrogen losses, due to the higher amount of N accumulated in stable forms in the soil due to biological N₂-fixation and N root compartimentation. On the other hand tree competition for light, water and nutrients eventually could limit legume growth and N₂-fixation. The isotopic method based on ¹⁵N natural abundance is one of the most used methods to assess Biological Nitrogen Fixation (BNF). The B-value, that is defined as the δ¹⁵N value of a legume when completely dependent on N₂-fixation for satisfying its N demand, is of primary importance for BNF estimations. The B-value may vary with species, plant age at harvest and growing conditions, e.g. light availability. Therefore, the B-value found in literature could not be representative for all legumes and environments, in particular for legumes grown intercropped with trees and thus subject to shading conditions. In this pot experiment we assessed the B-value of several forage legumes, as affected by different levels of simulated shading and grown in N-free medium. A greenhouse pot experiment was established in March 2021 at the Department of Agriculture, Food and Environment (DAFE) of the University of Pisa to determine the B-value for ¹⁵N calculations about two forage legume species grown in a field trial located at the Center of Agri-Envirnomental Research “Enrico Avanzi” of the University of Pisa, San Piero a Grado (Pisa) (43°41'6.97"N 10°20'29.22"E), using the same shade treatments

1871(1875) Quirico Filopanti Studio per la Scuola-officina Italiana (da far nascere a Bologna utilizzando il lascito Aldini) trascrizione e commento di Pier Gabriele Molari

Fra le carte di Filopanti, conservate nella Biblioteca dell’Università di Bologna, vi è lo studio per la Scuola-officina Italiana da far nascere a Bologna. Filopanti espone lo studio nel 1871 a una Commissione costituita per capire come utilizzare il lascito Aldini. Lo studio cade inascoltato e quindi Filopanti lo ripresenta nel 1875, addirittura ampliandolo. Lo studio si legge tutto d’un fiato e piace riportare subito le impressioni, così come si ricordano, per poi, come Filopanti insegna, rileggerlo adagio e capirne lo schema che permetterà di assimilarlo e mandarlo a mente

Percepção do profissional de saúde sobre o atendimento de pacientes com quadros de somatização no serviço de emergência hospitalar

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Light reduction affected agronomic performance and nutritive value of temporary grassland swards in a Mediterranean rainfed plot trial

In Italy, traditional olive orchards are characterised by low tree density (100-300 ha-1) allowing the cultivation of forage and crops under the tree canopy (Paris et al., 2019). Eichhorn et al. (2006), reported that in Central Italy there are 20000 ha of farmland identified as a silvoarable olive orchard. The intercropping of perennial legumes and trees is a key strategy to improve nutrient cycle of silvoarable systems, due to the higher amount of nitrogen (N) accumulated in stable forms in soil due by biological nitrogen-fixation (Hernandez-Esteban et al., 2019; Sanna et al., 2019), leading to a request for reduction of inorganic N fertilisation. Perennial legumes can also provide a continuous soil cover during the entire year reducing soil loss risk (Vallebona et al., 2016). In the Mediterranean basin, the most important perennial legume is alfalfa (Medicago sativa L.). Previous studies reported that alfalfa nutritive value was not negatively affected by tree presence (Mantino et al., 2021), whereas legume production was reduced due the competition for resources such as water (Nasielski et al., 2015), nutrients (Isaac et al., 2014) and light (Mantino et al., 2021). In Tuscany, sulla (Hedysarum coronarium L.) an autochthonous biennial legume is appreciated for its rusticity, productivity, and quality and it is intercropped with Italian ryegrass (Lolium multiflorum Lam.) for a better utilisation as pasture. In 2019, a rainfed field plot trial was established to evaluate agronomic performance and nutritive value of different perennial forage species grown under different levels of light reduction, aiming to start a selection of shade tolerant forage crops. In October, the plot trial was established in Pisa, on a clay-loam soil with pH of 8.1 and 2.5 % w/w of organic matter content in the topsoil (0-0.3 m). Before sowing, 100 kg ha-1 of P2O5 were applied. The experimental layout complies with a two-factor randomized complete block design with four replicates (18 m2 sizing each plot). The first factor included five different swards: i) sulla cv. Silvan, (ii) ryegrass cv. Teanna, (iii) mix of sulla cv. Silvan and ryegrass, 50:50 (iv) mix of sulla cv. Silvan, sulla cv. Chiara Stella and sulla cv. Bellante 33:33:33 and (v) alfalfa cv. Messe. The second factor included three increasing shading levels: S0) the control representing full light availability, S25) and S50), corresponding to a reduction of potential light availability of 25 and 50% respectively. As previously tested by Varella et al. (2011), shading was provided by woody slats, N-S oriented, 2.0 m long and 0.10 m wide, with a distance between each slat of 0.10 m for S50 and 0.20 m for S25, covering a total surface of 4 m2. After sowing, slats were placed at 0.8 m above ground level. Yield and nutritive value of herbage mass and N2 fixation were evaluated for two consecutive years. Herbage biomass was not affected by the reduction of the 50% of light in ryegrass and ryegrass-sulla mixture while it was negatively affected in alfalfa and sulla. Conversely, the 25% of shade level had no effect on legume yield