8,247 research outputs found

    Cut-free Calculi and Relational Semantics for Temporal STIT Logics

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    We present cut-free labelled sequent calculi for a central formalism in logics of agency: STIT logics with temporal operators. These include sequent systems for Ldm , Tstit and Xstit. All calculi presented possess essential structural properties such as contraction- and cut-admissibility. The labelled calculi G3Ldm and G3Tstit are shown sound and complete relative to irreflexive temporal frames. Additionally, we extend current results by showing that also Xstit can be characterized through relational frames, omitting the use of BT+AC frames

    Direct Speech-to-Text Translation Models as Students of Text-to-Text Models

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    Direct speech-to-text translation (ST) is an emerging approach that consists in performing the ST task with a single neural model. Although this paradigm comes with the promise to outperform the traditional pipeline systems, its rise is still limited by the paucity of speech-translation paired corpora compared to the large amount of speech-transcript and parallel bilingual corpora available to train previous solutions. As such, the research community focused on techniques to transfer knowledge from automatic speech recognition (ASR) and machine translation (MT) models trained on huge datasets. In this paper, we extend and integrate our recent work (Gaido, Gangi, et al. 2020) analysing the best performing approach to transfer learning from MT, which is represented by knowledge distillation (KD) in sequence-to-sequence models. After the comparison of the different KD methods to understand which one is the most effective, we extend our previous analysis of the effects – both in terms of benefits and drawbacks – to different language pairs in high-resource conditions, ensuring the generalisability of our findings. Altogether, these extensions complement and complete our investigation on KD for speech translation leading to the following overall findings: i) the best training recipe involves a word-level KD training followed by a fine-tuning step on the ST task, ii) word-level KD from MT can be detrimental for gender translation and can lead to output truncation (though these problems are alleviated by the fine-tuning on the ST task), and iii) the quality of the ST student model strongly depends on the quality of the MT teacher model, although the correlation is not linear

    Idmb: a tool for navigating the Inspire data model and generating an Inspire SQL database and WFS Configuration

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    The Inspire Data Model Browser (IDMB) is a free tool that performs the following functions: (i) it presents the Inspire UML Data Model as a tree-based structure, which is complementary to the UML diagrams; (ii) it generates a Postgis SQL Script for creating an INSPIRE compliant SQL database (Inspire Database) and a configuration file for the Deegree tool that enables the access to the Inspire Database through a Web Feature Service (WFS) producing GML according to the Inspire XML Schemas

    What factors affect the selection of industrial wastewater treatment configuration?

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    Industrial wastewater treatment is gaining significance in literature due to stricter environmental policies and increased environmental awareness. The selection of the wastewater configuration encompasses both the treatment as well as several decisions around wastewater collection and disposal pertaining industrial decision-making sphere. However, so far in the wastewater literature, research has mostly discussed either technical features of wastewater technologies, or wastewater policy issues at broader level, without focusing on the industrial decision-making issues and driving factors leading to the selection of a specific configuration. Starting from a literature review, the present study provides an innovative framework of the possible options for wastewater system configuration, as well as major adoption factors by industrial decision-makers. The factors have been classified according to 7 categories, namely: influent-related, technological, economic/financial, internal socio-cultural, external socio-cultural, regulation, site characteristics. The framework, validated with acknowledgeable experts, policy makers and firms, has been preliminarily applied to Italian and Australian food firms. Our investigation reveals that the framework was able to include all relevant problems faced by industries in the selection of a treatment system configuration; besides, the relative importance of factors has been assessed: legal requirements emerge as the most critical factors, followed by volume and discharge fee, the latter particularly interesting for policy makers purposes, since it may guide the decision-making process. Further, the wastewater volume seems to play a key role in our exploratory investigation, with smaller firms preferring a complete off-site treatment to reduce the complexity, whilst larger firms preferring instead more partial or complete on-site treatment configurations for compliance costs reduction. In conclusion, we have provided policy and managerial implications stemming from the study as well as sketched interesting future research avenues

    From Finite to Linear Elastic Fracture Mechanics by Scaling

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    In the setting of finite elasticity we study the asymptotic behaviour of a crack that propagates quasi-statically in a brittle material. With a natural scaling of size and boundary conditions we prove that for large domains the evolution with finite elasticity converges to the evolution with linearized elasticity. In the proof the crucial step is the (locally uniform) convergence of the non-linear to the linear energy release rate, which follows from the combination of several ingredients: the Γ\Gamma-convergence of re-scaled energies, the strong convergence of minimizers, the Euler-Lagrange equation for non-linear elasticity and the volume integral representation of the energy release

    A versatile modular plant for converting biogas into advanced biofuels

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    The patented technology is a novel, portable, non-invasive, and flexible technical solution for converting biogas into valuable chemical compounds, such as bio-methanol and bio-dimethyl ether (bio-DME). It consists of compact modules, connected through a flange-valve-flange system, to be installed downstream of an existing traditional biogas plant. The two main sections of the module are those of reforming and synthesis: in the first, the biogas is converted into bio-syngas (H2/CO/CO2), while in the second the bio-syngas is transformed into advanced biofuels such as bio-methanol and bio-DME. Parts of the synthesis module can permanently be changed with small investments to switch the final products, according to local market needs and price volatilities. Downstream at the synthesis section, it is possible to add a module for separating and purifying the chemical products. The technology has been validated at the 0.15 MWe industrial scale
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