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We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axial tumors with diverse radiologic and anatomical presentation and a propensity for multiplicity. Nine participating teams each developed deep-learning automated segmentation models using image data from the largest multi-institutional systematically expert annotated multilabel multi-sequence meningioma MRI dataset to date, which included 1000 training set cases, 141 validation set cases, and 283 hidden test set cases. Each case included T2, T2/FLAIR, T1, and T1Gd brain MRI sequences with associated tumor compartment labels delineating enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Participant automated segmentation models were evaluated and ranked based on a scoring system evaluating lesion-wise metrics including dice similarity coefficient (DSC) and 95% Hausdorff Distance. The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0.976, 0.976, and 0.964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0.899, 0.904, and 0.871, respectively. These results serve as state-of-the-art benchmarks for future pre-operative meningioma automated segmentation algorithms. Additionally, we found that 1286 of 1424 cases (90.3%) had at least 1 compartment voxel abutting the edge of the skull-stripped image edge, which requires further investigation into optimal pre-processing face anonymization steps., Comment: 16 pages, 11 tables, 10 figures, MICCAI

Despite Portuguese being one of the most spoken languages in the world, there is a lack of high-quality information retrieval datasets in that language. We present Quati, a dataset specifically designed for the Brazilian Portuguese language. It comprises a collection of queries formulated by native speakers and a curated set of documents sourced from a selection of high-quality Brazilian Portuguese websites. These websites are frequented more likely by real users compared to those randomly scraped, ensuring a more representative and relevant corpus. To label the query-document pairs, we use a state-of-the-art LLM, which shows inter-annotator agreement levels comparable to human performance in our assessments. We provide a detailed description of our annotation methodology to enable others to create similar datasets for other languages, providing a cost-effective way of creating high-quality IR datasets with an arbitrary number of labeled documents per query. Finally, we evaluate a diverse range of open-source and commercial retrievers to serve as baseline systems. Quati is publicly available at https://huggingface.co/datasets/unicamp-dl/quati and all scripts at https://github.com/unicamp-dl/quati ., Comment: 22 pages

Land use expansion is linked to major sustainability concerns including climate change, food security and biodiversity loss. This expansion is largely concentrated in so-called frontiers, defined here as places experiencing marked transformations due to rapid resource exploitation. Understanding the mechanisms shaping these frontiers is crucial for sustainability. Previous work focused mainly on explaining how active frontiers advance, in particular into tropical forests. Comparatively, our understanding of how frontiers emerge in territories considered marginal in terms of agricultural productivity and global market integration remains weak. We synthesize conceptual tools explaining resource and land-use frontiers, including theories of land rent and agglomeration economies, of frontiers as successive waves, spaces of territorialization, friction, and opportunities, anticipation and expectation. We then propose a new theory of frontier emergence, which identifies exogenous pushes, legacies of past waves, and actors anticipations as key mechanisms by which frontiers emerge. Processes of abnormal rent creation and capture and the built-up of agglomeration economies then constitute key mechanisms sustaining active frontiers. Finally, we discuss five implications for the governance of frontiers for sustainability. Our theory focuses on agriculture and deforestation frontiers in the tropics, but can be inspirational for other frontier processes including for extractive resources, such as minerals.

This paper describes how motivational models can be used to cross check agile requirements artifacts to improve consistency and completeness of software requirements. Motivational models provide a high level understanding of the purposes of a software system. They complement personas and user stories which focus more on user needs rather than on system features. We present an exploratory case study sought to understand how software engineering students could use motivational models to create better requirements artifacts so they are understandable to non-technical users, easily understood by developers, and are consistent with each other. Nine consistency principles were created as an outcome of our study and are now successfully adopted by software engineering students at the University of Melbourne to ensure consistency between motivational models, personas, and user stories in requirements engineering., Comment: 9 pages, 2 figures, SERP'21 - The 19th International Conference on Software Engineering Research and Practice

The last decades have witnessed an unprecedented advancement in our knowledge of the large scale universe. In particular, increasingly accurate cosmological observations have allowed us to discover a form of "dark energy", which presently dominates the expansion of the universe. On the other hand, fundamental problems in the standard cosmological model point towards the possibility of a primordial inflationary period. Both these expansion phases have in common the fact that they should be governed by forms of energy with properties much similar to those of vacuum energy of classical or quantum fields. In the meanwhile, quantum field theory in curved spaces (QFTCS) has proved a rich framework to analyze phenomena of a quantum nature in regimes where spacetime curvature is relevant, but not too extreme; particularly, it yields novel insights on the structure and dynamics of quantum vacuum. In this dissertation, we make a thorough exposition of the fundamentals of QFTCS and present some of its applications in cosmological spacetimes. Particular attention is given to the construction of an empirical notion of particles through an idealized model of particle detectors, and to the phenomenon of particle creation in expanding FLRW spacetimes. Further, we develop the procedure of adiabatic renormalization, and use it to compute the renormalized stress tensor in these spacetimes. For a noninteracting scalar field in de Sitter spaces, we find that it takes the form of a cosmological constant, although a quantitatively self-consistent value with the background expansion can only be found at Planckian densities. We also present a construction of a simple inflationary model, driven by a self-interacting classical scalar field, and show how the quantized fluctuations of this field could give rise to a nearly scale-invariant power spectrum, like the one that is currently observed in the CMB., Comment: 246 pages

With the advent of Intelligent Transportation Systems (ITS), data from diverse sensors either embedded into the vehicles or present along with the smart city infrastructure, are of utmost importance and require both processing power and efficient trust mechanisms for information exchange in vehicle-to-everything (V2X) communications. To accomplish these requirements, both edge computing and blockchain have been recently adopted towards a secure, distributed, and computation empowered Internet of Vehicles (IoV). This paper surveys prominent solutions for blockchain-based vehicular edge computing (VEC), provides a taxonomy, highlights their main features, advantages, and limitations to provide subsidies for further proposals., Comment: 6 pages, 2 pictures and 1 table (IEEE International Conference on Advanced Networks and Telecommunications Systems - Workshop on New Advances on Vehicle-to-Everything (V2X) Communications and Networking, 14-17 December 2020)

We consider the ground state and the low-lying excitations of dipolar Bose-Einstein condensates in a bubble trap, i.e., a shell-shaped spherically symmetric confining potential. By means of an appropriate Gaussian ansatz, we determine the ground-state properties in the case where the particles interact by means of both the isotropic and short-range contact and the anisotropic and long-range dipole-dipole potential in the thin-shell limit. Moreover, with the ground state at hand, we employ the sum-rule approach to study the monopole, the two-, the three-dimensional quadrupole as well as the dipole modes. We find situations in which neither the virial nor Kohn's theorem can be applied. On top of that, we demonstrate the existence of anisotropic particle density profiles, which are absent in the case with repulsive contact interaction only. These significant deviations from what one would typically expect are then traced back to both the anisotropic nature of the dipolar interaction and the novel topology introduced by the bubble trap.