Appalti e corruzione: alcune evidenze sulla penetrazione criminale negli appalti di lavori

Sommario: 1. Premessa. – 2. Costruzione dataset e nuove misure di criminalità negli ap- palti. – 3. Evoluzione del contesto normativo e descrizione dei meccanismi di sele- zione dei contraenti privati. – 4. Analisi descrittiva. – 5. Metodologia econometri- ca. – 6. Risultati. – 7. Conclusioni e suggerimenti di policy

Energy-Constrained Delivery of Goods with Drones Under Varying Wind Conditions

In this paper, we study the feasibility of sending drones to deliver goods from a depot to a customer by solving what we call the Mission-Feasibility Problem (MFP). Due to payload constraints, the drone can serve only one customer at a time. To this end, we propose a novel framework based on time-dependent cost graphs to properly model the MFP and tackle the delivery dynamics. When the drone moves in the delivery area, the global wind may change thereby affecting the drone's energy consumption, which in turn can increase or decrease. This issue is addressed by designing three algorithms, namely: (i) compute the route of minimum energy once, at the beginning of the mission, (ii) dynamically reconsider the most convenient trip towards the destination, and (iii) dynamically select only the best local choice. We evaluate the performance of our algorithms on both synthetic and real-world data. The changes in the drone's energy consumption are reflected by changes in the cost of the edges of the graphs. The algorithms receive the new costs every time the drone flies over a new vertex, and they have no full knowledge in advance of the weights. We compare them in terms of the percentage of missions that are completed with success (the drone delivers the goods and comes back to the depot), with delivered (the drone delivers the goods but cannot come back to the depot), and with failure (the drone neither delivers the goods nor comes back to the depot).Comment: typo author's nam

DNA base editing corrects common Hemophilia A mutations and restores factor VIII expression in vitro and ex-vivo models

Background: Replacement and non-replacement therapies effectively control bleedings in Hemophilia A (HA) but imply lifelong interventions. The authorized gene addition therapy could provide a cure but still poses questions on durability. F8 gene correction would definitively restore factor VIII (FVIII) production, as shown in animal models through nucleases mediating homologous recombination (HR). However, low efficiency and potential off-target double-strand break (DSB) still limit HR translatability. Objectives: To correct common model single point mutations leading to severe HA through the recently developed DSB/HR-independent base (BE) and prime (PE) editing approaches. Methods: Screening for efficacy of BE/PE systems in HEK293T transiently expressing FVIII variants and validation at DNA (sequencing) and protein (ELISA; aPTT) level in stable clones. Evaluation of rescue in engineered blood outgrowth endothelial cells (BOEC) by lentiviral-mediated delivery of BE. Results and conclusions: Transient assays identified the best-performing BE/PE systems for each variant, with the highest rescue of FVIII expression (up to 25% of rFVIIIwt) for the p.R2166* and p.R2228Q mutations. In stable clones we demonstrated that the mutation reversion on DNA (∼24%) was consistent with the rescue of FVIII secretion and activity 20-30%). The lentiviral-mediated delivery of the selected BE systems was attempted in engineered BOEC harboring the p.R2166* and p.R2228Q variants, which led to an appreciable and dose-dependent rescue of secreted functional FVIII. Overall data provide the first proof-of-concept for effective BE/PE-mediated correction of HA-causing mutations, which encourage studies in mouse models to develop a personalized cure for large cohorts of patients though a single intervention

Optimal Routing Schedules for Robots Operating in Aisle-Structures

In this paper, we consider the Constant-cost Orienteering Problem (COP) where a robot, constrained by a limited travel budget, aims at selecting a path with the largest reward in an aisle-graph. The aisle-graph consists of a set of loosely connected rows where the robot can change lane only at either end, but not in the middle. Even when considering this special type of graphs, the orienteering problem is known to be NP-hard. We optimally solve in polynomial time two special cases, COP-FR where the robot can only traverse full rows, and COP-SC where the robot can access the rows only from one side. To solve the general COP, we then apply our special case algorithms as well as a new heuristic that suitably combines them. Despite its light computational complexity and being confined into a very limited class of paths, the optimal solutions for COP-FR turn out to be competitive even for COP in both real and synthetic scenarios. Furthermore, our new heuristic for the general case outperforms state-of-art algorithms, especially for input with highly unbalanced rewards

Network Sensitivity of Systemic Risk

A growing body of studies on systemic risk in financial markets has emphasized the key importance of taking into consideration the complex interconnections among financial institutions. Much effort has been put in modeling the contagion dynamics of financial shocks, and to assess the resilience of specific financial markets - either using real network data, reconstruction techniques or simple toy networks. Here we address the more general problem of how shock propagation dynamics depends on the topological details of the underlying network. To this end we consider different realistic network topologies, all consistent with balance sheets information obtained from real data on financial institutions. In particular, we consider networks of varying density and with different block structures, and diversify as well in the details of the shock propagation dynamics. We confirm that the systemic risk properties of a financial network are extremely sensitive to its network features. Our results can aid in the design of regulatory policies to improve the robustness of financial markets

Dispatching Point Selection For A Drone-based Delivery System Operating In A Mixed Euclidean–Manhattan Grid

In this paper, we present a drone-based delivery system that assumes to deal with a mixed-area, i.e., two areas, one rural and one urban, placed side-by-side. In the mixed-areas, called EM-grids, the distances are measured with two different metrics, and the shortest path between two destinations concatenates the Euclidean and Manhattan metrics. Due to payload constraints, the drone serves a single customer at a time returning back to the dispatching point (DP) after each delivery to load a new parcel for the next customer. In this paper, we present the 1 -Median Euclidean–Manhattan grid Problem (MEMP) for EM-grids, whose goal is to determine the drone\u27s DP position that minimizes the sum of the distances between all the locations to be served and the point itself. We study the MEMP on two different scenarios, i.e., one in which all the customers in the area need to be served (full-grid) and another one where only a subset of these must be served (partial-grid). For the full-grid scenario we devise optimal and approximation algorithms, while for the partial-grid scenario we devise an optimal algorithm

Interplay between competitive and cooperative interactions in a three-player pathogen system

In ecological systems, heterogeneous interactions between pathogens take place simultaneously. This occurs, for instance, when two pathogens cooperate, while at the same time, multiple strains of these pathogens co-circulate and compete. Notable examples include the cooperation of human immunodeficiency virus with antibiotic-resistant and susceptible strains of tuberculosis or some respiratory infections with Streptococcus pneumoniae strains. Models focusing on competition or cooperation separately fail to describe how these concurrent interactions shape the epidemiology of such diseases. We studied this problem considering two cooperating pathogens, where one pathogen is further structured in two strains. The spreading follows a susceptible-infected-susceptible process and the strains differ in transmissibility and extent of cooperation with the other pathogen. We combined a mean-field stability analysis with stochastic simulations on networks considering both well-mixed and structured populations. We observed the emergence of a complex phase diagram, where the conditions for the less transmissible, but more cooperative strain to dominate are non-trivial, e.g. non-monotonic boundaries and bistability. Coupled with community structure, the presence of the cooperative pathogen enables the coexistence between strains by breaking the spatial symmetry and dynamically creating different ecological niches. These results shed light on ecological mechanisms that may impact the epidemiology of diseases of public health concern

A Drone-Based Application for Scouting Halyomorpha Halys Bugs in Orchards with Multifunctional Nets

In this work, we consider the problem of using a drone to collect information within orchards in order to scout insect pests, i.e., the stink bug Halyomorpha halys. An orchard can be modeled as an aisle-graph, which is a regular and constrained data structure formed by consecutive aisles where trees are arranged in a straight line. For monitoring the presence of bugs, a drone flies close to the trees and takes videos and/or pictures that will be analyzed offline. As the drone\u27s energy is limited, only a subset of locations in the orchard can be visited with a fully charged battery. Those places that are most likely to be infested should be selected to promptly detect the pest. We implemented the proposed approach on a DJI drone and evaluated its performance in the real-world environment