Collisions of self-bound quantum droplets

We report on the study of binary collisions between quantum droplets formed by an attractive mixture of ultracold atoms. We distinguish two main outcomes of the collision, i.e. merging and separation, depending on the velocity of the colliding pair. The critical velocity $v_c$ that discriminates between the two cases displays a different dependence on the atom number $N$ for small and large droplets. By comparing our experimental results with numerical simulations, we show that the non-monotonic behavior of $v_c(N)$ is due to the crossover from a compressible to an incompressible regime, where the collisional dynamics is governed by different energy scales, i.e. the droplet binding energy and the surface tension. These results also provide the first evidence of the liquid-like nature of quantum droplets in the large $N$ limit, where their behavior closely resembles that of classical liquid droplets

Facing War: Rethinking Europe's Security and Defence

Russia’s attack on Ukraine has sent shockwaves across Europe and the world. While the current war is a geopolitical turning point, it remains unclear whether it will trigger a quantum leap forward for European defence policies and for the role of the European Union as a security provider. This Report investigates whether we can expect a further convergence of European strategic cultures, and on collaboration among Europeans to generate the required military capabilities and integrate their forces. Most importantly, it finds that the timely implementation of the EU’s Strategic Compass will be a decisive test to establish whether Europeans are rising to the challenge of taking more responsibility for their security and defence.Publishe

coupling effects on the dynamic response of moored floating platforms for offshore wind energy plants

Abstract The increasing importance of offshore deep-water wind energy together with the complexity of the wind-wave-structure interaction problem makes the dynamic analysis of floating platforms a case of considerable interest. In this work, the dynamics of moored floating platforms for deep-water wind energy purposes is analysed in regular waves in order to discuss the effects on the motion due to the coupling of different degrees of freedom, usually associated with the operation of the mooring system and the hydrodynamic action, and the role of the main parameters affecting the motion. The platform is modelled as a rigid body and the associated differential dynamic problem is solved by using a suitable Lie group time integrator. The loads associated with mooring lines and waves are respectively assessed through a quasi-static model and a linear hydrodynamic model. The coupling of different degrees of freedom is usually related to loads with higher-frequency components and non-zero mean value that could bring the system into a mean dynamic configuration rather different from the static equilibrium configuration. Moreover, very interesting to limit the oscillations of the body is the effect of the location of the center of mass, the lower the center the lower the amplitude of pitch and roll response

Who becomes an entrepreneur? The role of ability, education, and sector choice

The classical occupational choice model does not explain the simultaneous existence of low and high ability entrepreneurs. In this paper, we study the decision to become an entrepreneur when individuals choose their education level and the economic sector where to operate. We distinguish two sectors: the knowledge and the traditional sector. The knowledge sector requires individuals to invest in education. Under this framework, two results are possible: one where only high ability individuals become entrepreneurs, and one with the coexistence of low and high ability entrepreneurs. This framework provides a rational explanation of the relationship between ability, education, and self-employment. Using PIAAC data, we test the empirical implications of the model. We find that most countries have an equilibrium with low and high ability entrepreneurs

On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology

Message Passing Neural Networks (MPNNs) are instances of Graph Neural Networks that leverage the graph to send messages over the edges. This inductive bias leads to a phenomenon known as over-squashing, where a node feature is insensitive to information contained at distant nodes. Despite recent methods introduced to mitigate this issue, an understanding of the causes for over-squashing and of possible solutions are lacking. In this theoretical work, we prove that: (i) Neural network width can mitigate over-squashing, but at the cost of making the whole network more sensitive; (ii) Conversely, depth cannot help mitigate over-squashing: increasing the number of layers leads to over-squashing being dominated by vanishing gradients; (iii) The graph topology plays the greatest role, since over-squashing occurs between nodes at high commute (access) time. Our analysis provides a unified framework to study different recent methods introduced to cope with over-squashing and serves as a justification for a class of methods that fall under `graph rewiring'.Comment: Accepted to ICML23; 21 page

Negative Pigment Network Identifies a Peculiar Melanoma Subtype and Represents a Clue to Melanoma Diagnosis: A Dermoscopic Study of 401 Melanomas

The dermoscopic descriptor "negative pigment network" (NPN) has been reported in several types of melanocytic and non-melanocytic lesions, although it has a higher frequency of association with melanoma and Spitz naevus. In a study of 401 consecutive melanomas, excluding facial, acral and mucosal locations, the frequency and variability of NPN were investigated, and the results of NPN correlated with clinical and histopathological data. NPN of any extension was found in 27% of melanomas, most frequently invasive and arising from a naevus on the trunk of young subjects. Seven percent of melanomas in the study population showed presence of NPN in more than half of the lesion area; most of these did not show typical dermoscopic melanoma features. The authors propose a new melanoma subtype, in which extensive NPN should be considered as a diagnostic indicator

Role of Strain Elastography and Shear-Wave Elastography in a Multiparametric Clinical Approach to Indeterminate Cytology Thyroid Nodules

BACKGROUND In thyroid nodules with indeterminate cytology, further clinical assessment aimed at ruling out malignancy is often mandatory. Ancillary imaging techniques and genetic mutation analysis can improve the risk stratification of such lesions, thereby facilitating the clinician's decision to undertaken surgery or simple follow-up. The aim of this study was to evaluate the diagnostic performance of shear-wave elastography (SW), strain elastography (ELX 2/1), conventional ultrasound (US), contrast-enhanced ultrasound (CEUS), and BRAF V600E mutation analysis in the aforementioned lesions. MATERIAL AND METHODS We enrolled 81 patients, each with 1 indeterminate-cytology thyroid nodule. Thyroid function, thyroperoxidase antibodies and calcitonin were known in each case. SW, ELX 2/1, US, CEUS, and BRAF mutation analysis were subsequently performed, followed by a second FNAB. If the lesion was not downgraded to benign, surgery was recommended and histological reports collected. RESULTS There were 28 nodules (34%) that proved benign on the second FNAB; 38 nodules (47%) underwent surgery (17 benign, 21 malignant), and 15 nodules (19%) refused surgery. The only techniques related to histological outcome were US (AUC=0,766), ELX 2/1 (AUC=0.701), and BRAF analysis (AUC=0.762). ELX 2/1 and SW reports were not correlated with each other (P=0.45). A scoring system taking into account all the variables considered performed better than the single variables alone (AUC=0.831). CONCLUSIONS In indeterminate-cytology thyroid lesions, repeating FNAB can avoid unnecessary surgery. ELX 2/1 seems to perform better than SW in distinguishing malignancy; these techniques could, however, be complementary in describing such lesions. A multiparametric approach appears the most accurate in predicting nodule histology