‘Urgenda-Style’ Strategic Climate Change Litigation in Italy: A Tale of Human Rights and Torts?

This contribution addresses the first strategic climate change litigation filed against the Italian State, the Giudizio Universale case. Giudizio Universale’s legal architecture is largely akin to other landmark cases filed in Europe, such as Urgenda in The Netherlands and Klimaatzaak in Belgium. Accordingly, Giudizio Universale is grounded on the state’s breach of international and EU obligations, the encroachment of human rights enshrined in the European Convention on Human Rights and the Italian Constitution, and the consequent attribution of domestic tort liability to the state under the Italian Civil Code. This article thus examines the main arguments raised in Giudizio Universale in light of the underlying domestic human rights and tort liability regimes. It first investigates the interplay between the breach of climate change obligations and human rights infringement as presented in the complaint to understand whether, and to what extent, Italian courts could give deference to an ‘Urgenda-style’ claim. Second, it unpacks the existing interpretation of tort liability as applied to state liability vis-à-vis its citizens by Italian courts. Third, it factors Giudizio Universale in the recent Italian Constitutional reform, which explicitly introduced the protection of the environment, biodiversity and ecosystems, as well as a reference to the ‘interests of future generations’, into the fundamental principles of the Italian Constitution. Overall, the article concludes that several limitations exist in the Italian legal system in the pursuance of strategic climate litigation against the state for its (in)action against climate change. One of the merits of the Giudizio Universale case, however, is that it challenges these limitations to provide another suitable tool for ensuring protection against the climate emergency

Not too big for its mouth: direct evidence of a macrodasyidan gastrotrich preyed in nature by a dileptid ciliate

Nearly ubiquitous and usually speciose in most aquatic habitats, the meiofaunal-sized gastrotrichs are recognized as an important component of marine and freshwater ecosystems. The common observations that gastrotrichs feed on bacteria, microalgae and biodetritus strongly imply that they play a relevant role in linking the microbial loop to the higher trophic levels. Which are the organisms that in turn prey on gastrotrichs is, however, a substantially unexplored question. Inspecting meiofauna samples collected from shallow sites of the Tyrrhenian coast, we had the chance to spot a wild case of a macrodasyidan gastrotrich predated by a dileptid ciliate. This case is documented here with a set of in-vivo photos, jointly with an unequivocal taxonomic identification of the preyed gastrotrich with Paraturbanella teissieri and a tentative identification of the predator ciliate with Pseudomonilicaryon marinus

Temporal blocking of finite-difference stencil operators with sparse "off-the-grid" sources

Stencil kernels dominate a range of scientific applications, including seismic and medical imaging, image processing, and neural networks. Temporal blocking is a performance optimization that aims to reduce the required memory bandwidth of stencil computations by re-using data from the cache for multiple time steps. It has already been shown to be beneficial for this class of algorithms. However, applying temporal blocking to practical applications' stencils remains challenging. These computations often consist of sparsely located operators not aligned with the computational grid (“off-the-grid”). Our work is motivated by modelling problems in which source injections result in wavefields that must then be measured at receivers by interpolation from the grided wavefield. The resulting data dependencies make the adoption of temporal blocking much more challenging. We propose a methodology to inspect these data dependencies and reorder the computation, leading to performance gains in stencil codes where temporal blocking has not been applicable. We implement this novel scheme in the Devito domain-specific compiler toolchain. Devito implements a domain-specific language embedded in Python to generate optimized partial differential equation solvers using the finite-difference method from high-level symbolic problem definitions. We evaluate our scheme using isotropic acoustic, anisotropic acoustic, and isotropic elastic wave propagators of industrial significance. After auto-tuning, performance evaluation shows that this enables substantial performance improvement through temporal blocking over highly-optimized vectorized spatially-blocked code of up to 1.6x

Full-waveform inversion, Part 3: Optimization

This tutorial is the third part of a full-waveform inversion (FWI) tutorial series with a step-by-step walkthrough of setting up forward and adjoint wave equations and building a basic FWI inversion framework. For discretizing and solving wave equations, we use Devito (http://www.opesci.org/devito-public), a Python-based domain-specific language for automated generation of finite-difference code (Lange et al., 2016). The first two parts of this tutorial (Louboutin et al., 2017, 2018) demonstrated how to solve the acoustic wave equation for modeling seismic shot records and how to compute the gradient of the FWI objective function using the adjoint-state method. With these two key ingredients, we will now build an inversion framework that can be used to minimize the FWI least-squares objective function

Combining checkpointing and data compression for large scale seismic inversion

Seismic inversion and imaging are adjoint-based optimization problems that processes up to terabytes of data, regularly exceeding the memory capacity of available computers. Data compression is an effective strategy to reduce this memory requirement by a certain factor, particularly if some loss in accuracy is acceptable. A popular alternative is checkpointing, where data is stored at selected points in time, and values at other times are recomputed as needed from the last stored state. This allows arbitrarily large adjoint computations with limited memory, at the cost of additional recomputations. In this paper we combine compression and checkpointing for the first time to compute a realistic seismic inversion. The combination of checkpointing and compression allows larger adjoint computations compared to using only compression, and reduces the recomputation overhead significantly compared to using only checkpointing

Assessment of myocardial extracellular volume on body computed tomography in breast cancer patients treated with anthracyclines

Background: Cancer treatment with anthracyclines may lead to an increased incidence of cardiac disease due to cardiotoxicity, as they may cause irreversible myocardial fibrosis. So far, the proposed methods for screening patients for cardiotoxicity have led to only limited success, while the analysis of myocardial extracellular volume (mECV) at cardiac magnetic resonance (CMR) has shown promising results, albeit requiring a dedicated exam. Recent studies have found strong correlations between mECV values obtained through computed tomography (CT), and those derived from CMR. Thus, our purpose was to evaluate the feasibility of estimating mECV on thoracic contrast-enhanced CT performed for staging or follow-up in breast cancer patients treated with anthracyclines, and, if feasible, to assess if a rise in mECV is associated with chemotherapy, and persistent over time. Methods: After ethics committee approval, female patients with breast cancer who had undergone at least 2 staging or follow-up CT examinations at our institution, one before and one shortly after the end of chemotherapy including anthracyclines were retrospectively evaluated. Patients without available haematocrit, with artefacts in CT images, or who had undergone radiation therapy of the left breast were excluded. Follow-up CT examinations at longer time intervals were also analysed, when available. mECV was calculated on scans obtained at 1, and 7 min after contrast injection. Results: Thirty-two female patients (aged 57\ub113 years) with pre-treatment haematocrit 38%\ub14%, and ejection fraction 64%\ub16% were analysed. Pre-treatment mECV was 27.0%\ub12.9% at 1 min, and 26.4%\ub13.8% at 7 min, similar to values reported for normal subjects in the literature. Post-treatment mECV (median interval: 89 days after treatment) was 31.1%\ub14.9%, and 30.0%\ub15.1%, respectively, values significantly higher than pre-treatment values at all times (P<0.005). mECV at follow-up (median interval: 135 days after post-treatment CT) was 31.0%\ub14.5%, and 27.7%\ub13.7%, respectively, without significant differences (P>0.548) when compared to post-treatment values. Conclusions: mECV values from contrast-enhanced CT scans could play a role in the assessment of myocardial condition in breast cancer patients undergoing anthracycline-based chemotherapy. CT-derived ECV could be an imaging biomarker for the monitoring of therapy-related cardiotoxicity, allowing for potential secondary prevention of cardiac damage, using data derived from an examination that could be already part of patients\u2019 clinical workflow

Towards self-verification in finite difference code generation

Code generation from domain-specific languages is becoming increasingly popular as a method to obtain optimised low-level code that performs well on a given platform and for a given problem instance. Ensuring the correctness of generated codes is crucial. At the same time, testing or manual inspection of the code is problematic, as the generated code can be complex and hard to read. Moreover, the generated code may change depending on the problem type, domain size, or target platform, making conventional code review or testing methods impractical. As a solution, we propose the integration of formal verification tools into the code generation process. We present a case study in which the CIVL verification tool is combined with the Devito finite difference framework that generates optimised stencil code for PDE solvers from symbolic equations. We show a selection of properties of the generated code that can be automatically specified and verified during the code generation process. Our approach allowed us to detect a previously unknown bug in the Devito code generation tool

Architecture and performance of Devito, a system for automated stencil computation

Stencil computations are a key part of many high-performance computing applications, such as image processing, convolutional neural networks, and finite-difference solvers for partial differential equations. Devito is a framework capable of generating highly-optimized code given symbolic equations expressed in Python, specialized in, but not limited to, affine (stencil) codes. The lowering process -- from mathematical equations down to C++ code -- is performed by the Devito compiler through a series of intermediate representations. Several performance optimizations are introduced, including advanced common sub-expressions elimination, tiling and parallelization. Some of these are obtained through well-established stencil optimizers, integrated in the back-end of the Devito compiler. The architecture of the Devito compiler, as well as the performance optimizations that are applied when generating code, are presented. The effectiveness of such performance optimizations is demonstrated using operators drawn from seismic imaging applications

Stride: a flexible software platform for high-performance ultrasound computed tomography

BACKGROUND AND OBJECTIVE: Advanced ultrasound computed tomography techniques like full-waveform inversion are mathematically complex and orders of magnitude more computationally expensive than conventional ultrasound imaging methods. This computational and algorithmic complexity, and a lack of open-source libraries in this field, represent a barrier preventing the generalised adoption of these techniques, slowing the pace of research, and hindering reproducibility. Consequently, we have developed Stride, an open-source Python library for the solution of large-scale ultrasound tomography problems. METHODS: On one hand, Stride provides high-level interfaces and tools for expressing the types of optimisation problems encountered in medical ultrasound tomography. On the other, these high-level abstractions seamlessly integrate with high-performance wave-equation solvers and with scalable parallelisation routines. The wave-equation solvers are generated automatically using Devito, a domain-specific language, and the parallelisation routines are provided through the custom actor-based library Mosaic. RESULTS: We demonstrate the modelling accuracy achieved by our wave-equation solvers through a comparison (1) with analytical solutions for a homogeneous medium, and (2) with state-of-the-art modelling software applied to a high-contrast, complex skull section. Additionally, we show through a series of examples how Stride can handle realistic numerical and experimental tomographic problems, in 2D and 3D, and how it can scale robustly from a local multi-processing environment to a multi-node high-performance cluster. CONCLUSIONS: Stride enables researchers to rapidly and intuitively develop new imaging algorithms and to explore novel physics without sacrificing performance and scalability. This will lead to faster scientific progress in this field and will significantly ease clinical translation