Long Run and Short Run Constraints in the Access to Private Health Care Services: Evidence from Selected European Countries

This paper aims at distinguishing long-run and short-run constraints in the access to private health care services. To this end, we apply the methodology proposed by Carneiro and Heckman (2003) to the SHARE database, a survey conducted in a number of European countries, involving some 22,000 individuals over the age of 50. Micro-data includes information on health and health consumption, and socioeconomic variables (like income and wealth). Our results show that the problem of short-run constraints in the access to private health care services could be real, especially in Italy, Greece, and to some extent Spain. Moreover, there appear to be differences in the role of credit constraints, both considering more specific services, and gender differences

Feature Selection for Classification with QAOA

Feature selection is of great importance in Machine Learning, where it can be used to reduce the dimensionality of classification, ranking and prediction problems. The removal of redundant and noisy features can improve both the accuracy and scalability of the trained models. However, feature selection is a computationally expensive task with a solution space that grows combinatorically. In this work, we consider in particular a quadratic feature selection problem that can be tackled with the Quantum Approximate Optimization Algorithm (QAOA), already employed in combinatorial optimization. First we represent the feature selection problem with the QUBO formulation, which is then mapped to an Ising spin Hamiltonian. Then we apply QAOA with the goal of finding the ground state of this Hamiltonian, which corresponds to the optimal selection of features. In our experiments, we consider seven different real-world datasets with dimensionality up to 21 and run QAOA on both a quantum simulator and, for small datasets, the 7-qubit IBM (ibm-perth) quantum computer. We use the set of selected features to train a classification model and evaluate its accuracy. Our analysis shows that it is possible to tackle the feature selection problem with QAOA and that currently available quantum devices can be used effectively. Future studies could test a wider range of classification models as well as improve the effectiveness of QAOA by exploring better performing optimizers for its classical step

Benchmarking Adaptative Variational Quantum Algorithms on QUBO Instances

In recent years, Variational Quantum Algorithms (VQAs) have emerged as a promising approach for solving optimization problems on quantum computers in the NISQ era. However, one limitation of VQAs is their reliance on fixed-structure circuits, which may not be taylored for specific problems or hardware configurations. A leading strategy to address this issue are Adaptative VQAs, which dynamically modify the circuit structure by adding and removing gates, and optimize their parameters during the training. Several Adaptative VQAs, based on heuristics such as circuit shallowness, entanglement capability and hardware compatibility, have already been proposed in the literature, but there is still lack of a systematic comparison between the different methods. In this paper, we aim to fill this gap by analyzing three Adaptative VQAs: Evolutionary Variational Quantum Eigensolver (EVQE), Variable Ansatz (VAns), already proposed in the literature, and Random Adapt-VQE (RA-VQE), a random approach we introduce as a baseline. In order to compare these algorithms to traditional VQAs, we also include the Quantum Approximate Optimization Algorithm (QAOA) in our analysis. We apply these algorithms to QUBO problems and study their performance by examining the quality of the solutions found and the computational times required. Additionally, we investigate how the choice of the hyperparameters can impact the overall performance of the algorithms, highlighting the importance of selecting an appropriate methodology for hyperparameter tuning. Our analysis sets benchmarks for Adaptative VQAs designed for near-term quantum devices and provides valuable insights to guide future research in this area

The runaway taxpayer

In order to analyse the determinants of tax evasion, the existing literature on individual tax compliance typically takes a prior-to-audit point of view. This paper focuses on a post-audit, post-detection -so far unexplored- framework, by investigating what happens after tax evasion has been discovered and noncompliant taxpayers are asked to pay their debts. We fi rst develop a two-period dynamic model of individual choice, considering an individual that has been already audited and detected as tax evader, who knows that Tax Authorities are looking for her to cash the due amount. We derive the optimal decision of running away in order to avoid paying the bill, and show that the experience of a prior tax notice reduces the probability to behave as a scofflaw. We then exploit information on post-audit, post-detection tax compliance provided by an Italian collection agency for the period 2004-2007 to empirically test the effectiveness of the prior notice against scofflaws. The evidence from alternative logit model speci cations supports our theoretical prediction: experiencing a tax notice reduces the probability of running away by about 10%. However, this may prove to be insufficient to discourage some individuals to runaway in order to avoid paying their dues

Exploring the link between diabetes and pancreatic cancer

Introduction: Epidemiological studies indicate an association between type 2 diabetes and pancreatic cancer but the complex and multidirectional relationship between them remains unclear. Areas covered: We summarized epidemiological evidence on diabetes and pancreatic cancer exploring the time-risk relationship. We described mechanisms linking long-standing diabetes to pancreatic cancer. We discussed pancreatic cancer-associated diabetes and its implication in the early detection of pancreatic cancer. Expert opinion: The markedly increased risk of pancreatic cancer in patients with new-onset diabetes compared with long-standing diabetes indicates a complex and bidirectional connection, with long-standing diabetes being a predisposing factor for pancreatic cancer (increasing the risk of the malignancy 1.5- to 2-fold) and new-onset diabetes an early manifestation of the tumour. Identifying clinical features and biomarkers to distinguish pancreatic cancer-associated diabetes from type 2 diabetes is an important goal to improve management and survival of this cancer. Imaging (MRI) for middle age patients with new-onset diabetes may be considered

Dynamic facial expressions of emotions are discriminated at birth

The ability to discriminate between different facial expressions is fundamental since the first stages of postnatal life. The aim of this study is to investigate whether 2-days-old newborns are capable to discriminate facial expressions of emotions as they naturally take place in everyday interactions, that is in motion. When two dynamic displays depicting a happy and a disgusted facial expression were simultaneously presented (i.e., visual preference paradigm), newborns did not manifest any visual preference (Experiment 1). Nonetheless, after being habituated to a happy or disgusted dynamic emotional expression (i.e., habituation paradigm), newborns successfully discriminated between the two (Experiment 2). These results indicate that at birth newborns are sensitive to dynamic faces expressing emotions

Molecular Profiling of Lymphatic Endothelial Cell Activation In Vitro

The lymphatic vascular system plays a key role in cancer progression. Indeed, the activation of lymphatic endothelial cells (LECs) through the lymphangiogenic process allows for the formation of new lymphatic vessels (LVs) that represent the major route for the dissemination of solid tumors. This process is governed by a plethora of cancer-derived and microevironmental mediators that strictly activate and control specific molecular pathways in LECs. In this work we used an in vitro model of LEC activation to trigger lymphangiogenesis using a mix of recombinant pro-lymphangiogenic factors (VFS) and a co-culture system with human melanoma cells. Both systems efficiently activated LECs, and under these experimental conditions, RNA sequencing was exploited to unveil the transcriptional profile of activated LECs. Our data demonstrate that both recombinant and tumor cell-mediated activation trigger significant molecular pathways associated with endothelial activation, morphogenesis, and cytokine-mediated signaling. In addition, this system provides information on new genes to be further investigated in the lymphangiogenesis process and open the possibility for further exploitation in other tumor contexts where lymphatic dissemination plays a relevant role

Hybrid modeling of a biorefinery separation process to monitor short-term and long-term membrane fouling

Membrane filtration is commonly used in biorefineries to separate cells from fermentation broths containing the desired products. However, membrane fouling can cause short-term process disruption and long-term membrane degradation. The evolution of membrane resistance over time can be monitored to track fouling, but this calls for adequate sensors in the plant. This requirement might not be fulfilled even in modern biorefineries, especially when multiple, tightly interconnected membrane modules are used. Therefore, characterization of fouling in industrial facilities remains a challenge. In this study, we propose a hybrid modeling strategy to characterize both reversible and irreversible fouling in multi-module biorefinery membrane separation systems. We couple a linear data-driven model, to provide high-frequency estimates of trans-membrane pressures from the available measurements, with a simple nonlinear knowledge-driven model, to compute the resistances of the individual membrane modules. We test the proposed strategy using real data from the world's first industrial biorefinery manufacturing 1,4-bio-butanediol via fermentation of renewable raw materials. We show how monitoring of individual resistances, even when done by simple visual inspection, offers valuable insight on the reversible and irreversible fouling state of the membranes. We also discuss the advantage of the proposed approach, over monitoring trans-membrane pressures and permeate fluxes, from the standpoints of data variability, effect of process changes, interaction between module in multi-module systems, and fouling dynamics

The effect of co-payments on the take-up of prenatal tests

Noninvasive prenatal screening tests help identify genetic disorders in a fetus, but their take-up remains low in several countries. Using a regression discontinuity design, we test the causal effect of a policy that eliminated co-payments for noninvasive screening tests in Italy. We identify the treatment effects by a discontinuity in women's eligibility for a free test based on their conception date. We find that the policy increases the probability of women's undergoing noninvasive screening tests by 5.5 percentage points, and the effect varies by socioeconomic status. We do not find evidence of substitution effects with more expensive and riskier invasive diagnostic tests. In addition, the increase in take-up does not affect pregnancy termination or newborn health. We find some evidence of positive effects on mothers’ health behaviors during pregnancy as measured by reductions in mothers’ weight gain and hospital admissions during pregnancy, but these are statistically significant only at the 10 percent level

Osteochondritis dissecans of the knee: Epidemiology, etiology, and natural history.

Osteochondritis dissecans of the knee is a disease that typically affects skeletally immature patients. Clinically manifested with knee pain, limping, and joint disfunction, this condition has remained misunderstood and undervalued for a long period. Although being a rare condition, its awareness is of utmost clinical interest because of the possible severe consequences it can bring when misrecognized or inadequately treated. Its etiology remains unclear and is still debated. Many theories have been proposed, including inflammation, local ischemia, subchondral ossification abnormalities, genetic factors, and repetitive mechanical microtrauma, with a likely interplay of the same. This review article aims to deliver and discuss current and up-to-date concepts on epidemiology, etiology, and natural history of this pediatric condition. Level of evidence: level V