A meta-learning approach for training explainable graph neural networks

In this article, we investigate the degree of explainability of graph neural networks (GNNs). The existing explainers work by finding global/local subgraphs to explain a prediction, but they are applied after a GNN has already been trained. Here, we propose a meta-explainer for improving the level of explainability of a GNN directly at training time, by steering the optimization procedure toward minima that allow post hoc explainers to achieve better results, without sacrificing the overall accuracy of GNN. Our framework (called MATE, MetA-Train to Explain) jointly trains a model to solve the original task, e.g., node classification, and to provide easily processable outputs for downstream algorithms that explain the model's decisions in a human-friendly way. In particular, we meta-train the model's parameters to quickly minimize the error of an instance-level GNNExplainer trained on-the-fly on randomly sampled nodes. The final internal representation relies on a set of features that can be ``better'' understood by an explanation algorithm, e.g., another instance of GNNExplainer. Our model-agnostic approach can improve the explanations produced for different GNN architectures and use any instance-based explainer to drive this process. Experiments on synthetic and real-world datasets for node and graph classification show that we can produce models that are consistently easier to explain by different algorithms. Furthermore, this increase in explainability comes at no cost to the accuracy of the model

Singing to infants matters: early singing interactions affect musical preferences and facilitate vocabulary building

This research revealed that the frequency of reported infant-parent singing interactions predicted 6-month-old infants' performance in laboratory music experiments and mediated their language development in the second year. At 6 months, infants (n=36) were tested using a preferential listening procedure assessing their sustained attention to instrumental and sung versions of the same novel tunes whilst the parents completed an ad-hoc questionnaire assessing home musical interactions with their infants. Language development was assessed with a follow-up when the infants were 14-month-old (n=26). The main results showed that 6-month-olds preferred listening to sung rather than instrumental melodies, and that self-reported high levels of parental singing with their infants[i] were associated with less pronounced preference for the sung over the instrumental version of the tunes at 6 months, and [ii] predicted significant advantages on the language outcomes in the second year. The results are interpreted in relation to conceptions of developmental plasticity

Re-identification of objects from aerial photos with hybrid siamese neural networks

In this paper, we consider the task of re-identifying the same object in different photos taken from separate positions and angles during aerial reconnaissance, which is a crucial task for the maintenance and surveillance of critical large-scale infrastructure. To effectively hybridize deep neural networks with available domain expertise for a given scenario, we propose a customized pipeline, wherein a domain-dependent object detector is trained to extract the assets (i.e., sub-components) present on the objects, and a siamese neural network learns to re-identify the objects, exploiting both visual features (i.e., the image crops corresponding to the assets) and the graphs describing the relations among their constituting assets. We describe a real-world application concerning the re-identification of electric poles in the Italian energy grid, showing our pipeline to significantly outperform siamese networks trained from visual information alone. We also provide a series of ablation studies of our framework to underline the effect of including topological asset information in the pipeline, learnable positional embeddings in the graphs, and the effect of different types of graph neural networks on the final accuracy

A breach in plant defences: Pseudomonas syringae pv. actinidiae targets ethylene signalling to overcome Actinidia chinensis pathogen responses

Ethylene interacts with other plant hormones to modulate many aspects of plant metabolism, including defence and stomata regulation. Therefore, its manipulation may allow plant pathogens to overcome the host’s immune responses. This work investigates the role of ethylene as a virulence factor for Pseudomonas syringae pv. actinidiae (Psa), the aetiological agent of the bacterial canker of kiwifruit. The pandemic, highly virulent biovar of this pathogen produces ethylene, whereas the biovars isolated in Japan and Korea do not. Ethylene production is modulated in planta by light/dark cycle. Exogenous ethylene application stimulates bacterial virulence, and restricts or increases host colonisation if performed before or after inoculation, respectively. The deletion of a gene, unrelated to known bacterial biosynthetic pathways and putatively encoding for an oxidoreductase, abolishes ethylene production and reduces the pathogen growth rate in planta. Ethylene production by Psa may be a recently and independently evolved virulence trait in the arms race against the host. Plantand pathogen-derived ethylene may concur in the activation/suppression of immune responses, in the chemotaxis toward a suitable entry point, or in the endophytic colonisation

Topological conditions for discrete symmetry breaking and phase transitions

In the framework of a recently proposed topological approach to phase transitions, some sufficient conditions ensuring the presence of the spontaneous breaking of a Z_2 symmetry and of a symmetry-breaking phase transition are introduced and discussed. A very simple model, which we refer to as the hypercubic model, is introduced and solved. The main purpose of this model is that of illustrating the content of the sufficient conditions, but it is interesting also in itself due to its simplicity. Then some mean-field models already known in the literature are discussed in the light of the sufficient conditions introduced here

A congenital anterior urethrocutaneous fistula in a boy whose mother was exposed to ionizing radiations: a case report and literature review

Anterior congenital urethrocutaneous fistula is a rare anomaly that may present in an isolated fashion or in association with other anomalies of the genital urinary tract or anorectal malformations. A case of congenital anterior urethrocutaneous fistula nonassociated with other congenital anomalies in a 3-year-old male whose mother has been exposed to Chernobyl's nuclear fallout is described. The patient was successfully operated with no recurrence. We report a review of the literature about etiology and surgical strategy including the role of ionizing radiations. The congenital anterior urethrocutaneous fistula represents a rare malformation. The etiopathogenesis is unknown

Automated detection of lung nodules in low-dose computed tomography

A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector computed-tomography (CT) images has been developed in the framework of the MAGIC-5 Italian project. One of the main goals of this project is to build a distributed database of lung CT scans in order to enable automated image analysis through a data and cpu GRID infrastructure. The basic modules of our lung-CAD system, consisting in a 3D dot-enhancement filter for nodule detection and a neural classifier for false-positive finding reduction, are described. The system was designed and tested for both internal and sub-pleural nodules. The database used in this study consists of 17 low-dose CT scans reconstructed with thin slice thickness (~300 slices/scan). The preliminary results are shown in terms of the FROC analysis reporting a good sensitivity (85% range) for both internal and sub-pleural nodules at an acceptable level of false positive findings (1-9 FP/scan); the sensitivity value remains very high (75% range) even at 1-6 FP/scanComment: 4 pages, 2 figures: Proceedings of the Computer Assisted Radiology and Surgery, 21th International Congress and Exhibition, Berlin, Volume 2, Supplement 1, June 2007, pp 357-35

Spatio-temporal dynamics in semiconductor microresonators with thermal effects.

In this paper we study the dynamics of the intracavity field, carriers and lattice temperature in externally driven semiconductor microcavities. The combination/competition of the different time-scales of the dynamical variables together with diffraction and carrier/thermal diffusions are responsible for new dynamical behaviors. We report here the occurrence of a spatio-temporal instability of the Hopf type giving rise to Regenerative Oscillations and travelling patterns and cavity solitons

Process integration study of tail-end Ca-Looping process for CO2capture in cement plants

In this work, the integration of Calcium looping (CaL) process into a cement plant for post-combustion CO2capture is assessed via process simulations. In the proposed scheme, the carbonator of the CaL process is used as an end-of-pipe unit to capture the CO2from the cement kiln gas. From the results obtained, it is demonstrated that CO2capture efficiencies of the order of 90% are achievable, with CaL reactors operating in conditions not far from those demonstrated for application in power plants. The integration of the tail-end CaL process results in a significant increase of the total fuel consumption (about two to three times higher) compared to the benchmark cement plant without CO2capture. On the other hand, the heat from the CaL process can be recovered by a steam cycle producing decarbonized electric power that may exceed the needs of the plant auxiliaries (including the ASU and the CO2compression and purification unit), exporting in this way electricity to the grid and so resulting in CO2emission credits from a life cycle perspective. The resulting specific primary energy consumption for CO2avoided (SPECCA) highly depends on the reference power generation technology considered, and it ranges between 2.7 and 3.7 MJLHV/kgCO2in a coal-fired power generation scenario. As for the retrofittability of existing cement plants, the operation of the suspension preheating tower after the implementation of the CaL unit, as well as the position of the CaL carbonator with respect to the raw mill, have been assessed. Based on the results obtained, no critical issues have been found from a technical point of view in the adoption of the tail-end CaL process in existing cement kilns