Design-based mapping for finite populations of marked points

The estimation of marks for a finite population of points scattered onto a study region is considered when a sample of these points is selected by a probabilistic sampling scheme. At each point, the mark is estimated by means of an inverse distance weighting interpolator. The design-based asymptotic properties of the resulting maps are derived when the study area remains fixed, a sequence of nested populations with increasing size is considered and samples of increasing size are selected. Conditions ensuring design-based asymptotic unbiasedness and consistency are given. They essentially require that marks are the values of a pointwise or uniformly continuous deterministic function, the enlargement of the populations is rather regular and the sequence of sampling designs ensures an asymptotic spatial balance. A computationally simple mean squared error estimator is proposed. A simulation study is performed to assess the theoretical results on artificial populations. Finally, an application for mapping the values of the height of trees in a forest stand located in North Italy is reported

The Development of Deep and Short Sea Shipping Container Routes Departing from Italian Ports

In this paper, an analysis of the development of Deep Sea Shipping (DSS) and Short Sea Shipping (SSS) container routes calling at Italian ports, is carried out. Data about DSS routes have been collected in the years: 2011, 2014, 2018 and 2019, while data about SSS services have been collected in 2010 and 2018. Italian ports have been classified as follows: Ligurian multi-port gateway cluster, which is formed by Leghorn, La Spezia, Genoa, Savona/Vado Ligure; Northern Adriatic multi-port gateway cluster, made up of Ancona, Ravenna, Venice and Trieste; Campanian multi-port gateway cluster, composed of Naples and Salerno; hub ports, i.e. Gioia Tauro, Cagliari (only until 2018) and Taranto (only until 2014). The most important gateway cluster, for both DSS and SSS services, is the Ligurian one which includes Genoa which is by far the major Italian container gateway port. Genoa has shown an almost constant increase in container traffic in the time period analyzed. Italian hub ports are also an important group, but they have registered a negative trend in the years under analysis. DSS routes, to Far East and the American Continent, usually call at the Ligurian ports and the hub port of Gioia Tauro. Northern Adriatic ports are crossed by only a few DSS routes, but they are crossed by a large number of SSS routes, especially feeder ones, with transshipment mainly in the hub ports of Gioia Tauro, Marsaxlokk, Piraeus and Port Said. The evolution of DSS services shows clearly the effects of naval gigantism phenomenon: the number of DSS services has decreased, but the total and, especially, the average DWT have increased. As regards SSS routes, also their frequencies have decreased, but their length and, in particular, the number of ports called, have increased: this choice is performed by container operators in order to increase the ships ’load factor’

Integral estimates for transport densities

The integration-by-parts methods introduced in this paper improve upon the Lp estimates on transport densities given in the recent paper by L. De Pascale and A. Pratelli (Calc. Var. Partial Differential Equations 14 (2002) 249–274)

A Preliminary Investigation of Machine Learning Approaches for Mobility Monitoring from Smartphone Data

In this work we investigate the use of machine learning models for the management and monitoring of sustainable mobility, with particular reference to the transport mode recognition. The specific aim is to automatize the detection of the user’s means of transport among those considered in the data collected with an App installed on the users smartphones, i.e. bicycle, bus, train, car, motorbike, pedestrian locomotion. Preliminary results show the potentiality of the analysis for the introduction of reliable advanced, machine learning based, monitoring systems for sustainable mobility. © 2020, Springer Nature Switzerland AG

Factors affecting the development of Bovine Respiratory Disease: a cross-sectional study in beef steers shipped from France to Italy

Bovine respiratory disease (BRD) is a complex, multifactorial syndrome and one of the major welfare and economical concerns for the cattle industry. This 1-year cross-sectional study was aimed at documenting the prevalence of BRD-related pathogens and clinical signs before and after a long journey and at identifying possible predisposition factors. Male Limousine beef steers (n = 169) traveling from France to Italy were health checked and sampled with Deep Nasopharyngeal Swabs (DNS) at loading (T0) and 4 days after arrival (T1). Real-time quantitative PCR was used to quantify the presence of bovine viral diarrhea virus (BVDV), bovine respiratory syncytial virus (BRSV), bovine alphaherpesvirus 1 (BoHV-1), bovine coronavirus (BCoV), bovine adenovirus (BAdV), bovine parainfluenza virus 3 (BPIV-3), Histophilus somni, Mannheimia haemolytica, Mycoplasma bovis, and Pasteurella multocida. Weather conditions at departure and arrival were recorded, and the travel conditions were taken from the travel documentation. At T0, even if no animals displayed clinical signs, some of them were already positive for one or more pathogens. At T1, the number of animals displaying clinical signs and positive for BCoV, BAdV, BRSV, H. somni, M. haemolytica, M. bovis, and P. multocida increased dramatically (p < 0.001). Transport also significantly increased co-infection passing from 16.0% at T0 to 82.8% at T1 (p < 0.001). An extra stop during the journey seemed to favor BRSV, M. haemolytica, and P. multocida (p < 0.05). Weather conditions, in particular sudden climate changes from departure to arrival and daily temperature variance, were found to be predisposing factors for many of the pathogens. The farm of arrival also played a role for BRSV, BAdV, and H. somni (p < 0.05). BCoV increased dramatically, but no associations were found confirming that it spreads easily during transport phases. Our findings increased our understanding of factors increasing the likelihood of BRD-related pathogens shedding and can be useful to minimize the incidence of BRD and to implement animal transport regulations

Low haemoglobin level predicts early hospital readmission in patients with cirrhosis and acute decompensation

Background & Aims: Patients with decompensated cirrhosis present frequent hospitalisations with a relevant clinical and socio-economic impact. This study aims to characterise unscheduled readmissions up to 1-year follow-up and identify predictors of 30-day readmission after an index hospitalisation for acute decompensation (AD). Methods: We performed a secondary analysis of a prospectively collected cohort of patients admitted for AD. Laboratory and clinical data at admission and at discharge were collected. Timing and causes of unscheduled readmissions and mortality were recorded up to 1 year. Results: A total of 329 patients with AD were included in the analysis. Acute-on-chronic liver failure was diagnosed in 19% of patients at admission or developed in an additional 9% of patients during the index hospitalisation. During the 1-year follow-up, 182 patients (55%) were rehospitalised and 98 (30%) more than once. The most frequent causes of readmission were hepatic encephalopathy (36%), ascites (22%), and infection (21%). Cumulative incidence of readmission was 20% at 30 days, 39% at 90 days, and 63% at 1 year. Fifty-four patients were readmitted for emergent liver-related causes within 30 days. Early readmission was associated with a higher 1-year mortality (47 vs. 32%, p = 0.037). Multivariable Cox regression analysis showed that haemoglobin (Hb) ≤8.7 g/dl (hazard ratio 2.63 [95% CI 1.38–5.02], p = 0.003) and model for end-stage liver disease-sodium score (MELD-Na) >16 at discharge (hazard ratio 2.23 [95% CI 1.27–3.93], p = 0.005), were independent predictors of early readmission. In patients with MELD-Na >16 at discharge, the presence of Hb ≤8.7 g/dl doubles the risk of early rehospitalisation (44% vs. 22%, p = 0.02). Conclusion: Besides MELD-Na, a low Hb level (Hb ≤8.7 g/dl) at discharge emerged as a new risk factor for early readmission, contributing to identification of patients who require closer surveillance after discharge. Impact and Implications: Patients with decompensated cirrhosis face frequent hospitalisations. In the present study, type and causes of readmissions were analysed during 1-year follow-up in patients discharged after the index hospitalisation for an acute decompensation of the disease. Early (30-day) liver-related readmission was associated with higher 1-year mortality. The model for end-stage liver disease-sodium score and low haemoglobin at discharge were identified as independent risk factors for early readmissions. Haemoglobin emerged as a new easy-to-use parameter associated with early readmission warranting further investigation

Phase field approach to optimal packing problems and related Cheeger clusters

In a fixed domain of $\Bbb{R}^N$ we study the asymptotic behaviour of optimal clusters associated to $\alpha$-Cheeger constants and natural energies like the sum or maximum: we prove that, as the parameter $\alpha$ converges to the "critical" value $\Big (\frac{N-1}{N}\Big ) _+$, optimal Cheeger clusters converge to solutions of different packing problems for balls, depending on the energy under consideration. As well, we propose an efficient phase field approach based on a multiphase Gamma convergence result of Modica-Mortola type, in order to compute $\alpha$-Cheeger constants, optimal clusters and, as a consequence of the asymptotic result, optimal packings. Numerical experiments are carried over in two and three space dimensions

Statistical inference on the h-index with an application to top-scientist performance

Despite the huge amount of literature on h-index, few papers have been devoted to the statistical analysis of h-index when a probabilistic distribution is assumed for citation counts. The present contribution relies on showing the available inferential techniques, by providing the details for proper point and set estimation of the theoretical h-index. Moreover, some issues on simultaneous inference - aimed to produce suitable scholar comparisons - are carried out. Finally, the analysis of the citation dataset for the Nobel Laureates (in the last five years) and for the Fields medallists (from 2002 onward) is proposed.Comment: 14 pages, 3 table

A glimpse into the differential topology and geometry of optimal transport

This note exposes the differential topology and geometry underlying some of the basic phenomena of optimal transportation. It surveys basic questions concerning Monge maps and Kantorovich measures: existence and regularity of the former, uniqueness of the latter, and estimates for the dimension of its support, as well as the associated linear programming duality. It shows the answers to these questions concern the differential geometry and topology of the chosen transportation cost. It also establishes new connections --- some heuristic and others rigorous --- based on the properties of the cross-difference of this cost, and its Taylor expansion at the diagonal.Comment: 27 page