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International audience; The association of left ventricular ejection fraction (LVEF) with procedural and long-term outcomes after state-of-the-art percutaneous coronary intervention (PCI) of bifurcation lesions remains unsettled. A total of 5,333 patients who underwent contemporary coronary bifurcation PCI were included in the intercontinental retrospective combined insights from the unified RAIN (veRy thin stents for patients with left mAIn or bifurcatioN in real life) and COBIS (COronary BIfurcation Stenting) III bifurcation registries. Of 5,003 patients (93.8%) with known baseline LVEF, 244 (4.9%) had LVEF

This work aims at distilling a systematic methodology to modernize existing sequential scientific codes with a little re-designing effort, turning an old codebase into modern code, i.e., parallel and robust code. We propose a semi-automatic methodology to parallelize scientific applications designed with a purely sequential programming mindset, possibly using global variables, aliasing, random number generators, and stateful functions. We demonstrate that the same methodology works for the parallelization in the shared memory model (via OpenMP), message passing model (via MPI), and General Purpose Computing on GPU model (via OpenACC). The method is demonstrated parallelizing four real-world sequential codes in the domain of physics and material science. The methodology itself has been distilled in collaboration with MSc students of the Parallel Computing course at the University of Torino, that applied it for the first time to the project works that they presented for the final exam of the course. Every year the course hosts some special lectures from industry representatives, who present how they use parallel computing and offer codes to be parallelized.

Summary Background The accuracy of current prediction tools for ischaemic and bleeding events after an acute coronary syndrome (ACS) remains insufficient for individualised patient management strategies. We developed a machine learning-based risk stratification model to predict all-cause death, recurrent acute myocardial infarction, and major bleeding after ACS. Methods Different machine learning models for the prediction of 1-year post-discharge all-cause death, myocardial infarction, and major bleeding (defined as Bleeding Academic Research Consortium type 3 or 5) were trained on a cohort of 19 826 adult patients with ACS (split into a training cohort [80%] and internal validation cohort [20%]) from the BleeMACS and RENAMI registries, which included patients across several continents. 25 clinical features routinely assessed at discharge were used to inform the models. The best-performing model for each study outcome (the PRAISE score) was tested in an external validation cohort of 3444 patients with ACS pooled from a randomised controlled trial and three prospective registries. Model performance was assessed according to a range of learning metrics including area under the receiver operating characteristic curve (AUC). Findings The PRAISE score showed an AUC of 0·82 (95% CI 0·78–0·85) in the internal validation cohort and 0·92 (0·90–0·93) in the external validation cohort for 1-year all-cause death; an AUC of 0·74 (0·70–0·78) in the internal validation cohort and 0·81 (0·76–0·85) in the external validation cohort for 1-year myocardial infarction; and an AUC of 0·70 (0·66–0·75) in the internal validation cohort and 0·86 (0·82–0·89) in the external validation cohort for 1-year major bleeding. Interpretation A machine learning-based approach for the identification of predictors of events after an ACS is feasible and effective. The PRAISE score showed accurate discriminative capabilities for the prediction of all-cause death, myocardial infarction, and major bleeding, and might be useful to guide clinical decision making. Funding None.

We investigate the effects of an institutional mechanism that incentivizes taxpayers to blow the whistle on collusive corruption and tax compliance. We explore this through a formal leniency program. In our experiment, we nest collusive corruption within a tax evasion framework. We not only study the effect of the presence of such a mechanism on behavior, but also the dynamic effect caused by the introduction and the removal of leniency. We find that in the presence of a leniency mechanism, subjects collude and accept bribes less often while paying more taxes, but there is no increase in bribe offers. Our results show that the introduction of the opportunity to blow the whistle decreases the collusion and bribe acceptance rate, and increases the collected tax yield. It also does not encourage bribe offers. In contrast, the removal of the institutional mechanism does not induce negative effects, suggesting a positive spillover effect of leniency that persists even after the mechanism has been removed.

Several complementary methods able to visualize the internal structures of eyes are used in the clinical practice in the diagnosis of pathologies affecting a specific zone of the eye. Despite the significant technological progress, the visualization of the entire eyeball at micrometric resolution is yet an unsolved task both in clinical diagnostics and in laboratory research. With this respect, high resolution 3D images of the eyeball would be extremely useful, in the study of various pathologies of the retina, the lens, and of the optic nerve. In this work we combined the state-of-the-art of micro computed tomography technology with phase-contrast imaging, a recent highly sensitive technique well adapted to investigate soft tissues without the use of contrast agents; we applied the technique in the post-mortem analysis of monkey eyes, which share several similitudes with the human organ. We reported here vascular, nervous and anatomical details of monkey eyes imaged with a 3.1 × 3.1 × 3.1 µm3 voxel size as well as the first 3D visualisation of the entire globe of Macaca’s fascicularis eye. Results have also been compared with, and validated by, histological analysis.

We analyzed decision making under risk in a group of 50 poor individuals and a group of 50 rich individuals from the city of Lima, Peru, using the Columbia Card Task game. Contrary to the decisions of the rich, the decisions of the poor were insensitive to changes in the magnitude of potential losses: the risk taking of the poor did not increase when potential losses were low compared to when they were high. The decisions of the poor were also significantly less sensitive to changes in the probability of potential losses, compared to those of the rich. On the contrary, similarly to the decisions of the rich, the decisions of the poor were significantly sensitive to changes in the gain amount: risk taking was higher when the gain amount was higher than when it was lower. The rich sample from Lima showed a similar pattern of risk-taking behavior as other non-poor populations from previous studies. Furthermore, the poor scored higher on the perceived constraints scale and showed the same level of unrealistic optimism for negative events, but less unrealistic optimism for positive events, than the rich.

This paper studies whether and how differently projected information about the impact of the Covid-19 pandemic affects individuals' prosocial behavior and expectations on future outcomes. We conducted an online experiment with British participants (N=961) when the UK introduced its first lockdown and the outbreak was on its growing stage. Participants were primed with either the environmental or economic consequences (i.e., negative primes), or the environmental or economic benefits (i.e., positive primes) of the pandemic, or with neutral information. We measured priming effects on an incentivized take-and-give dictator game and on participants' expectations about future environmental quality and economic growth. Our results show that primes affect participants' expectations, but not their prosociality. In particular, participants primed with environmental consequences hold a more pessimistic view on future environmental quality, while those primed with economic benefits are more optimistic about future economic growth. Instead, the positive environmental prime and the negative economic prime do not influence expectations. Our results offer insights into how information affects behavior and expectations during the Covid-19 pandemic.

Background Dense and unbiased cellular-resolution representations of extended volumetric central nervous system soft-tissue anatomy are difficult to obtain, even in experimental post-mortem settings. Interestingly, X-ray phase-contrast computed tomography (X-PCI-CT), an emerging soft-tissue-sensitive volumetric imaging technique, can provide multiscale organ- to cellular-level morphological visualizations of neuroanatomical structure. New Method Here, we tested different nervous-tissue fixation procedures, conventionally used for transmission electron microscopy, to better establish X-PCI-CT-specific sample-preparation protocols. Extracted rat spinal medullas were alternatively fixed with a standard paraformaldehyde-only aldehyde-based protocol, or in combination with glutaraldehyde. Some specimens were additionally post-fixed with osmium tetroxide. Multiscale X-PCI-CT datasets were collected at several synchrotron radiation facilities, using state-of-the-art setups with effective image voxel sizes of 3.03 to 0.33 μm3, and compared to high-field magnetic resonance imaging, histology and vascular fluorescence microscopy data. Results Multiscale X-PCI-CT of aldehyde-fixed spinal cord specimens resulted in dense histology-like volumetric representations and quantifications of extended deep spinal micro-vascular networks and of intra-medullary cell populations. Osmium post-fixation increased intra-medullary contrast between white and gray-matter tissues, and enhanced delineation of intra-medullary cellular structure, e.g. axon fibers and motor neuron perikarya. Comparison with Existing Methods Volumetric X-PCI-CT provides complementary contrast and higher spatial resolution compared to 9.4 T MRI. X-PCI-CT’s advantage over planar histology is the volumetric nature of the cellular-level data obtained, using samples much larger than those fit for volumetric vascular fluorescence microscopy. Conclusions Deliberately choosing (post-)fixation protocols tailored for optimal nervous-tissue structural preservation is of paramount importance in achieving effective and targeted neuroimaging via the X-PCI-CT technique.

Arguably, for many citizens the perceived expected disutility from sanctions is smaller than the monetary gain from tax evasion. Nevertheless most people pay their taxes most of the time. In a lab experiment, we show that the willingness to pay taxes even absent enforcement is indeed pronounced. Yet voluntary compliance is reduced if participants learn that income is heterogeneous. The effect is driven by participants with the lowest income. The reduction obtains irrespective of the tax regime. If the tax is proportional to income, or progressive, participants become more skeptical about the willingness of participants with high income to comply.

Most people pay their taxes most of the time, even if the expected disutility from enforcement is too low to deter tax evasion. One potential reason is tax morale and, more specifically, rule following. In a lab experiment, we show that the willingness to pay taxes just because participants are told they are supposed to pay is indeed pronounced. Yet compliance is reduced if participants learn that income is heterogeneous. The effect is driven by participants with the lowest income. The reduction obtains irrespective of the tax regime. If the tax is proportional to income, or progressive, participants become more skeptical about the willingness of participants with high income to comply.

Experimental and empirical literature on individual decision-making has shown a remarkable difference between planning and ongoing decisions: when asked to plan their actions, people overweight events with low probability; on the contrary, in ongoing decisions, they tend to ignore them. We report on a laboratory experiment designed to explore the presence of this decisional inconsistency in taxpayers’ behavior, by means of a commitment system for compliance. In line with the overweighting of events with small probabilities (i.e. fiscal audits), we find that planning induces the majority of people not only to adopt a mechanism of commitment to tax compliance, but also to actually comply.

When the phenomenon of tax evasion is discussed, both scholars and authorities agree on the fact that, although essential, classical enforcements are not enough to ensure tax compliance: some other forms of incentives must be adopted. The paper�s aim is to experimentally test the role of different non- monetary incentives for tax compliance: participants have been treated with different experimental conditions, which differ in the role played by anonymity. Indeed, subjects have been informed on the possibility of revealing their identity and their choices through the publication of their pictures, as a consequence of the result of the auditing process. As expected, anonymity plays an important role in the decision to pay taxes; in addition, we find that negative non-monetary incentive increases tax compliance more effectively than positive non-monetary incentive. We find also that the effect of these non-monetary incentives is mitigated, when too many information are made available. Finally, results show that, when evasion is made public, tax-dodgers are willing to pay in order to keep secret their cheating behavior and avoid public shame.

We investigate the effects of an institutional mechanism that incentivizes taxpayers to blow the whistle on collusive corruption and tax compliance. We explore this through a formal leniency program. In our experiment, we nest collusive corruption within a tax evasion framework. We not only study the effect of the presence of such a mechanism on behavior, but also the dynamic effect caused by the introduction and the removal of leniency. We find that in the presence of a leniency mechanism, subjects collude and accept bribes less often while paying more taxes, but there is no increase in bribe offers. Our results show that the introduction of the opportunity to blow the whistle decreases the collusion and bribe acceptance rate, and increases the collected tax yield. It also does not encourage bribe offers. In contrast, the removal of the institutional mechanism does not induce negative effects, suggesting a positive spillover effect of leniency that persists even after the mechanism has been removed.

Previous research provides compelling evidence that defaults affect individual behaviour in several domains. However, evidence of their influence in strategic interaction is scant. We experimentally investigate the effect of defaults on contributions to a public good and attempt to shed light on potential channels through which they operate. Our main experimental findings show that defaults influence contribution behaviour: preference for a suggested contribution significantly increases when it is presented as the default. However, this effect seems not to operate primarily through information conveyance or expectations about others’ behaviour. Default contributions, thus, appear to have an attractive power that goes beyond recommendation signals and expectation influences.

Group membership is a powerful determinant of social behaviour in a variety of experimental games. Its effect may be channelled primarily via the beliefs of group members, or directly change their social preferences. We report an experiment with a prisoner's dilemma with multiple actions, in which we manipulate players’ beliefs and show that group identity has a consistent positive effect on cooperation only when there is common knowledge of group affiliation. We also test the robustness of the minimal group effect using three different manipulations: one manipulation fails to induce group identity, and we observe an unsystematic effect of group membership when knowledge of affiliation is asymmetric.

This paper investigates optimal audit programs in an economy populated by artificial agents. The behavior of the artificial agents is calibrated using data obtained from experiments on fiscal evasion made in northern Chile (Antofagasta) and northern Italy (Trento). We identify a tax collection policy that is optimal in the sense that its outperforms the tax payments made by the calibrated agents, using any other standard collection plans used by governments. We find that the design of an optimal audit scheme depends on three components: income distribution, the identification of patterns of behaviors and the number of times individuals are audited.