2,042 research outputs found
\u3ci\u3eTownshend v. Townshend\u3c/i\u3e & \u3ci\u3eButtar v. Buttar\u3c/i\u3e: Gifts, Exclusions, and Intentions
No full textThis comment looks at two fairly recent decisions by the Ontario Court of Appeal, Townshend v Townshend (2012 ONCA 868) and Buttar v Buttar (2013 ONCA 617) with respect to the courts\u27 handling of the exclusion of gifts under section 4(2) of Ontario\u27s Family Law Act (RSO 1990, c F.3). In Ontario, gifts made by third parties outside the marriage to one spouse may be excluded from the calculation of a spouse\u27s Net Family Property (NFP). Property may cease to be excludable if it is not kept separate or if it is used to the benefit of the family. In both Townshend and Buttar, the court had to grapple with fungible gifts and decide to what degree the gifts should be excluded from the NFP calculations. In both decisions, the courts relied upon a line of reasoning that placed too much weight on the intentions of the donor when deciding whether (or to what extent) to exclude the gifts while simultaneously undervaluing the subsequent behaviour of the donees after delivery of the gift. One worry these decisions raise is that, if donees of gifts may rely merely on the fact of a gift and not on their actions subsequent to delivery of the gift, litigants will become emboldened to find far more “gifts” among their property. Even more worrisome, however, is that the courts may be willing to grant exclusions regardless of post-delivery behaviour and thereby undermine the purpose of the NFP calculations: namely, as the preamble of the Family Law Act says, to allow the court to order an “equitable settlement of the affairs of the spouses”
Un' "impossibile coniunzione": la "Canzona di Bacco" di Lorenzo de' Medici
No full textPartendo da una nuova edizione del testo di “Quanto è bella giovinezza”, dotato di un puntuale commento, si intende dimostrare il grado di novità della “canzona”, che parve “mirabile” ai contemporanei in quanto in essa Lorenzo il Magnifico seppe schivare le pastoie di un messaggio troppo esasperatamente sessuale, per farlo confluire nell’alveo più naturale e moralmente accettabile della necessità di non buttar via il tempo, dunque di godere, allorquando si presentano e prima che inesorabilmente passino, dei doni dell’esistenza
Prospects for the Search of a Standard Model Higgs Boson in ATLAS using Vector Boson Fusion
No full textThe potential for the discovery of a Standard Model Higgs boson in the mass range m_H WW(*) and H --> tau tau decay modes have been performed using a realistic simulation of the expected detector performance. The results obtained demonstrate the large discovery potential in the H --> WW(*) decay channel and the sensitivity to Higgs boson decays into tau-pairs in the low mass region around 120 GeV/c^2.The potential for the discovery of a Standard Model Higgs boson in the mass range m_H < 2 m_Z in the vector boson fusion mode has been studied for the ATLAS experiment at the LHC. The characteristic signatures of additional jets in the forward regions of the detector and of low jet activity in the central region allow for an efficient background rejection. Analyses for the H -> WW and H -> tau tau decay modes have been performed using a realistic simulation of the expected detector performance. The results obtained demonstrate the large discovery potential in the H -> WW decay channel and the sensitivity to Higgs boson decays into tau-pairs in the low-mass region around 120 GeV
First tests of a novel radiation hard CMOS sensor process for Depleted Monolithic Active Pixel Sensors
No full textThe upgrade of the ATLAS [1] tracking detector for the High-Luminosity Large Hadron Collider (LHC) at CERN requires novel radiation hard silicon sensor technologies. Significant effort has been put into the development of monolithic CMOS sensors but it has been a challenge to combine a low capacitance of the sensing node with full depletion of the sensitive layer. Low capacitance brings low analog power. Depletion of the sensitive layer causes the signal charge to be collected by drift sufficiently fast to separate hits from consecutive bunch crossings (25 ns at the LHC) and to avoid losing the charge by trapping. This paper focuses on the characterization of charge collection properties and detection efficiency of prototype sensors originally designed in the framework of the ALICE Inner Tracking System (ITS) upgrade [2]. The prototypes are fabricated both in the standard TowerJazz 180nm CMOS imager process [3] and in an innovative modification of this process developed in collaboration with the foundry, aimed to fully deplete the sensitive epitaxial layer and enhance the tolerance to non-ionizing energy loss. Sensors fabricated in standard and modified process variants were characterized using radioactive sources, focused X-ray beam and test beams before and after irradiation. Contrary to sensors manufactured in the standard process, sensors from the modified process remain fully functional even after a dose of 10(15)n(eq)/cm(2), which is the the expected NIEL radiation fluence for the outer pixel layers in the future ATLAS Inner Tracker (ITk) [4]
Dataset for "Distortion/Interaction Analysis via Machine Learning"
No full textMachine learning (ML) has previously been applied to predict reaction barriers for a variety of different chemical reactions. This is seen as the end point for this type of study however, post-reaction barrier analysis/energy decomposition approaches can provide insight into chemical reactivity. One such approach that has previously been used to provide information on chemical reactivity, for cycloaddition reactions in particular, is distortion/interaction-activation strain analysis (DIAS). We demonstrate that ML can be coupled with cheap and rapid semi-empirical quantum mechanical methods (SQM) to predict distortion and interaction energies at a fraction of the computational cost associated with running density functional theory (DFT) calculations. This dataset includes all the structural data in the form of Gaussian16 (Revision A.03 and C.01) output files for the four datasets used in this work and, the literature dataset reactions.Ground state reactant and transition state geometries for dimethyl malonate Michael addition reactions were built using Schrödinger’s R-Group Enumeration. R-groups were placed on various different positions of the Michael acceptor; the position depended upon the molecules in question. All structures were built in Gaussian16 (Revisions A.03 and C.01) and were conformationally searched using Schrödinger’s MacroModel (version 12.7). All structures were subsequently optimised using Gaussian16 (Revisions A.03 and C.01) using AM1 and wB97X-D/def2-TZVP (IEFPCM=Water)//wB97X-D/def2-TZVP.
For distortion/interaction-activation strain calculations, python code (available on the associated GitHub page: https://github.com/the-grayson-group/distortion-interaction_ML) was used to separate the distorted reactant structures before single point energies were calculated using Gaussian16 (Revision C.01) using AM1 and the DFT level of theory used in the original transition structure calculation
Dataset for "Machine learning reaction barriers in low data regimes: a horizontal and diagonal transfer learning approach"
No full textMachine learning (ML) has previously been used to predict density functional theory (DFT) free energy reaction barriers on a variety of different reactions from semi-empirical quantum mechanical (SQM) inputs. These models can require expensive dataset curation and can struggle with generalisability outside of the datasets immediate chemical space. One such approach that can drastically lower the number of required training points is transfer learning (TL). We demonstrate that various TL techniques can be used to provide highly accurate results with a fraction of the training points required for standard ML, thus lowering the overall computational cost of barrier predictions. This dataset includes all the structural data in the form of Gaussian16 (Revision A.03 and C.01) output files for the Diels-Alder and [3+2] cycloaddition reactions used for this ML/TL analysis. This data archive also includes exemplar code for performing some standard ML from the manuscript.Ground state reactant and transition state geometries for Diels-Alder reactions were built using Schrödinger’s R-Group Enumeration. R-groups were placed on various different positions of both dienes and dienophiles; the position depended upon the molecules in question. All structures were built in Gaussian16 (Revisions A.03 and C.01) and were conformationally searched using Schrödinger’s MacroModel (version 12.7). All structures were subsequently optimised using Gaussian16 (Revisions A.03 and C.01) using three different molecular modelling methods (AM1, PM3, and wB97X-D/def2-TZVP). A subset of the reactions were also optimised with DSD-PBEP86-D3(BJ)/def2-TZVP.
The same process was used for the [3+2] reactions however, these reactions were only optimised at the AM1 and wB97X-D/def2-TZVP levels of theory
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