Potentiality-Actuality and Matter-Form

In this paper I shall argue that the two schemes and the respective theories in which they are imbedded are not equivalent in any important sense. Rather they are complementary schemes which, though individually insufficient to explain the problem of change as Aristotle recognized it, are jointly sufficient. I shall maintain that (I) hylomorphism is prior to actuality as an explanatory scheme, but (II) it fails to explain important data concerning change which actuality theory accounts for; finally (III) I shall briefly indicate how this account of the structural relations between hylomorphism and actuality theory meets certain objections and accords with certain facts about the historical development of Aristotle\u27s theories

Infinite stacking of alternating polyfluoroaryl rings and bromide anions

The crystal structure of 1-(4-bromo-2,3,5,6-tetrafluorophenyl)-3-benzylimidazolium bromide comprises columns of parallel bromotetrafluorophenyl rings with an interplanar distance of 6.936(6) Å separated by bromide anions

The application of time-series MODIS NDVI profiles for the acquisition of crop information across Afghanistan

We investigated and developed a prototype crop information system integrating 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data with other available remotely sensed imagery, field data, and knowledge as part of a wider project monitoring opium and cereal crops. NDVI profiles exhibited large geographical variations in timing, height, shape, and number of peaks, with characteristics determined by underlying crop mixes, growth cycles, and agricultural practices. MODIS pixels were typically bigger than the field sizes, but profiles were indicators of crop phenology as the growth stages of the main first-cycle crops (opium poppy and cereals) were in phase. Profiles were used to investigate crop rotations, areas of newly exploited agriculture, localized variation in land management, and environmental factors such as water availability and disease. Near-real-time tracking of the current years’ profile provided forecasts of crop growth stages, early warning of drought, and mapping of affected areas. Derived data products and bulletins provided timely crop information to the UK Government and other international stakeholders to assist the development of counter-narcotic policy, plan activity, and measure progress. Results show the potential for transferring these techniques to other agricultural systems

New Measurements with Stopped Particles at the LHC

Metastable particles are common in many models of new physics at the TeV scale. If charged or colored, a reasonable fraction of all such particles produced at the LHC will stop in the detectors and give observable out of time decays. We demonstrate that significant information may be learned from such decays about the properties (e.g. charge or spin) of this particle and of any other particles to which it decays, for example a dark matter candidate. We discuss strategies for measuring the type of decay (two- vs three-body), the types of particles produced, and the angular distribution of the produced particles using the LHC detectors. We demonstrate that with O(10-100) observed decay events, not only can the properties of the new particles be measured but indeed even the Lorentz structure of the decay operator can be distinguished in the case of three-body decays. These measurements can not only reveal the correct model of new physics at the TeV scale, but also give information on physics giving rise to the decay at energy scales far above those the LHC can probe directly.Comment: 31 pages, 6 figures. References added, updated to reflect recent experimental results, version accepted for publication in Physical Review

A Discriminative Model for Polyphonic Piano Transcription

We present a discriminative model for polyphonic piano transcription. Support vector machines trained on spectral features are used to classify frame-level note instances. The classifier outputs are temporally constrained via hidden Markov models, and the proposed system is used to transcribe both synthesized and real piano recordings. A frame-level transcription accuracy of 68% was achieved on a newly generated test set, and direct comparisons to previous approaches are provided

Survey and monitoring of opium poppy and wheat in Afghanistan: 2003-2009

An integrated application of remote-sensing technology was devised and applied in Afghanistan during 2003–2009 providing critical information on cereal and poppy cultivation and poppy eradication. The results influenced UK and international policy and counter-narcotics actions in Afghanistan

Transcribing Multi-Instrument Polyphonic Music With Hierarchical Eigeninstruments

This paper presents a general probabilistic model for transcribing single-channel music recordings containing multiple polyphonic instrument sources. The system requires no prior knowledge of the instruments present in the mixture (other than the number), although it can benefit from information about instrument type if available. In contrast to many existing polyphonic transcription systems, our approach explicitly models the individual instruments and is thereby able to assign detected notes to their respective sources. We use training instruments to learn a set of linear manifolds in model parameter space which are then used during transcription to constrain the properties of models fit to the target mixture. This leads to a hierarchical mixture-of-subspaces design which makes it possible to supply the system with prior knowledge at different levels of abstraction. The proposed technique is evaluated on both recorded and synthesized mixtures containing two, three, four, and five instruments each. We compare our approach in terms of transcription with (i.e., detected pitches must be associated with the correct instrument) and without source-assignment to another multi-instrument transcription system as well as a baseline non-negative matrix factorization (NMF) algorithm. For two-instrument mixtures evaluated with source-assignment, we obtain average frame-level F-measures of up to 0.52 in the completely blind transcription setting (i.e., no prior knowledge of the instruments in the mixture) and up to 0.67 if we assume knowledge of the basic instrument types. For transcription without source assignment, these numbers rise to 0.76 and 0.83, respectively