The Political Economy of EU Agri-environmental measures: An empirical Assessment at the Regional Level

The paper deals with the political economy determinants of EU agri-environmental measures (AEMs) applied by 59 regional/country units, during the 2001-2004 period. Five different groups of determinants, spanning from positive and negative externalities to political institutions, are highlighted and tested using an econometric model. The main results suggest that AEMs implementation is mostly affected by the strength of farm lobbies, political institutions and the demand for positive externalities. On the contrary, AEMs do not seem implemented by the willingness to address negative externalities.Agri-environmental Measures, Political Economy, EU Regions, Environmental Economics and Policy,

Implementation of EU Agri-Environmental Measures at the Regional Level: Economic and Political Constraints

In this paper we apply a political objective function approach developed by Salhofer and Glebe (2004) to explain the high variability of agri-environmental program implementation at the EU regional level. The analysis covers 55 EU regions during the period 2001-2002, using basic data extracted from the Common Monitoring Indicators collected by the UE Commission for the programme's evaluation process. The main results indicate that the area covered by agri-environmental programs increases in regions where budget constraints are less severe and where the social demand for environmental amenities is more relevant. Moreover, agri-environmental programs are negatively related to the participation opportunity cost and show a non linear relation with the farmer's political weight.agri-environmental measures, CAP, regional and agricultural policy, Environmental Economics and Policy, Q18, Q24, Q28,

Off-farm Labour Decision of Italian Farm Operators. Factor Markets Working Document No. 61, August 2013

This paper analyses the factors affecting off-farm labour decisions of Italian farm operators. Using micro-level data from the Farm Business Survey (REA) over the pre- and post-2003 CAP reform periods, we investigated the impact that operator, family, farm and market characteristics exert on these choices. Among other things, the paper focuses also on the differential impact of those variables for operators of smaller and larger holdings. The main results suggest that operator and family characteristics have a significant impact on the decision to participate in off-farm work more for smaller than for bigger farms. By contrast, farm characteristics are more relevant variables for bigger farms. In particular, decoupled farm payments, by increasing the marginal productivity of farm labour, lower the probability of working off the farm only in bigger farms, while coupled subsidies in pre-reform years do not have a significant impact on labour decisions. Finally, we show that, after accounting for the standard covariates, local and territorial labour market characteristics generally have a low effect on off-farm work operators’ choices

Patterns and Determinants of Off-Farm Migration: Transfer frictions and persistency of relative income gaps. Factor Markets Working Papers No. 36, February 2013

The inter-sectoral migration of agricultural labour is a complex but fundamental process of economic development largely affected by the growth of agricultural productivity and the evolution of the agricultural relative income gap. Theory and some recent anecdotal evidence suggest that as an effect of large fixed and sunk costs of out-farm migration, the productivity gap between the agricultural and non-agricultural sectors should behave non-monotonically or following a U-shaped evolution during economic development. Whether or not this relationship holds true across a sample of 38 developing and developed countries and across more than 200 EU regions was empirically tested. Results strongly confirm this relationship, which also emphasises the role played by national agricultural policy

Emergence of Lie Symmetries in Functional Architectures Learned by CNNs

In this paper we study the spontaneous development of symmetries in the early layers of a Convolutional Neural Network (CNN) during learning on natural images. Our architecture is built in such a way to mimic some properties of the early stages of biological visual systems. In particular, it contains a pre-filtering step l(0) defined in analogy with the Lateral Geniculate Nucleus (LGN). Moreover, the first convolutional layer is equipped with lateral connections defined as a propagation driven by a learned connectivity kernel, in analogy with the horizontal connectivity of the primary visual cortex (V1). We first show that the l(0) filter evolves during the training to reach a radially symmetric pattern well approximated by a Laplacian of Gaussian (LoG), which is a well-known model of the receptive profiles of LGN cells. In line with previous works on CNNs, the learned convolutional filters in the first layer can be approximated by Gabor functions, in agreement with well-established models for the receptive profiles of V1 simple cells. Here, we focus on the geometric properties of the learned lateral connectivity kernel of this layer, showing the emergence of orientation selectivity w.r.t. the tuning of the learned filters. We also examine the short-range connectivity and association fields induced by this connectivity kernel, and show qualitative and quantitative comparisons with known group-based models of V1 horizontal connections. These geometric properties arise spontaneously during the training of the CNN architecture, analogously to the emergence of symmetries in visual systems thanks to brain plasticity driven by external stimuli

Blood inflammatory indices in goats around kidding

AbstractThe transition period of goats is often characterized by serious metabolic problems, mainly before parturition. These troubles are related to negative energy balance status, however all causes are not totally defined. To improve the knowledge about pathogenesis in this phase we have monitored the changes of some blood indices of lipomobilization and inflammation. Six blood samples were collected from 10 primiparous and 25 multiparous "Camosciata delle Alpi" goats after morning milking. Samples were collected around 20 and 7 days before parturition and on days 0, 3, 6 and 12 of lactation. Albumin, total protein, haptoglobin, ceruloplasmin, total cholesterol, NEFA, β-OH-butyrate (BHB), Ca, Mg and Zn were determined. Goats were grouped according to their BHB level before parturition: low (≤0.6 mmol/l; LOB), average (0.6÷1.09; AVB) and high (≥1.09 mmol/l; HIB) level. Furthermore, the AVB group was divided according to plasma haptoglobin level before parturition: low (<0.5 g/l) or high. The statistical..

Impressive abrasion rates of marked pebbles on a coarse-clastic beach within a 13-month timespan

In this paper the abrasion rate on a coarse-clastic beach was evaluated by calculating the volume loss recorded on indigenous pebbles within a 13-month timespan. The experiment was carried out at Marina di Pisa (Italy) on an artificial beach that was built to counteract the erosion processes affecting this sector of the coast. A total of 240 marble pebbles (120 rounded and 120 angular) were marked using the RFID technology and injected on the beach. The volume loss measured after consecutive recovery campaigns was progressively increasing, reaching the maximum value after 13 months (61% overall). The average volume loss is consistent between rounded and angular pebbles at any time (59.3% and 64.2% after 13 months respectively), meaning that the roundness is not a primary control factor on abrasion rate. The pebbles that did not reach such abrasion rates after 8 and 10 months (volume loss less than 20%) were found at heights equal or greater than 2 m above mean sea level, on the crest of the storm berm that formed during the strongest storms. This implies that the highest wearing is achieved in the lower portion of the backshore, which is also the area that underwent major topographic modifications. Here, sea water action might also exert chemical influence on the pebbles, adding to the mechanical abrasion. The main result of this research, indicating an impressive volume loss on beach pebbles in a short timespan, could be of key importance for coastal managers. The optimization of coarse sediment beach nourishments is also relevant, taking into right consideration that the volume loss due to sediment abrasion might exceed 50% of the original fill volume just after 1 year in the most dynamic portion of the beach

A wireless sensor network framework for real-time monitoring of height and volume variations on sandy beaches and dunes

In this paper, the authors describe the realization and testing of a Wireless Sensor Network (WSN) framework aiming at measuring, remotely and in real time, the level variations of the sand layer of sandy beaches or dunes. The proposed framework is based on an innovative low cost sensing structure, able to measure the level variations with a 5-cm degree of precision and to locally transfer the acquired data through the ZigBee protocol. The described sensor is integrated in a wider ZigBee wireless sensor network architecture composed of an array of sensors that, arranged according to a grid layout, can acquire the same data at different points, allowing the definition of a dynamic map of the area under study. The WSN is connected to a local Global System for Mobile Communications (GSM) gateway that is in charge of data processing and transmission to a cloud infrastructure through a General Packet Radio Service (GPRS) connection. Data are then stored in a MySQL database and made available any time and anywhere through the Internet. The proposed architecture has been tested in a laboratory, to analyze data acquisition, processing timing and power consumption and then in situ to prove the effectiveness of the system. The described infrastructure is expected to be integrated in a wider IoT architecture including different typologies of sensors, in order to create a multi-purpose tool for the study of coastal erosive processes

Rectus Femoris Characteristics in Post Stroke Spasticity: Clinical Implications from Ultrasonographic Evaluation

In stroke survivors, rectus femoris (RF) spasticity is often implicated in gait pattern alterations such as stiff knee gait (SKG). Botulinum toxin type A (BoNT-A) is considered the gold standard for focal spasticity treatment. However—even if the accuracy of injection is crucial for BoNT-A efficacy—instrumented guidance for BoNT-A injection is not routinely applied in clinical settings. In order to investigate the possible implications of an inadequate BoNT-A injection on patients' clinical outcome, we evaluated the ultrasound-derived RF characteristics (muscle depth, muscle thickness, cross-sectional area and mean echo intensity) in 47 stroke survivors. In our sample, we observed wide variability of RF depth in both hemiparetic and unaffected side of included patients (0.44 and 3.54 cm and between 0.25 and 3.16 cm, respectively). Moreover, our analysis did not show significant differences between treated and non-treated RF in stroke survivors. These results suggest that considering the inter-individual variability in RF muscle depth and thickness, injection guidance should be considered for BoNT-A treatment in order to optimize the clinical outcome of treated patients. In particular, ultrasound guidance may help the clinicians in the long-term follow-up of muscle quality