1,011 research outputs found
The Screen representation of spin networks: 2D recurrence, eigenvalue equation for 6j symbols, geometric interpretation and Hamiltonian dynamics
This paper treats 6j symbols or their orthonormal forms as a function of two
variables spanning a square manifold which we call the "screen". We show that
this approach gives important and interesting insight. This two dimensional
perspective provides the most natural extension to exhibit the role of these
discrete functions as matrix elements that appear at the very foundation of the
modern theory of classical discrete orthogonal polynomials. Here we present 2D
and 1D recursion relations that are useful for the direct computation of the
orthonormal 6j, which we name U. We present a convention for the order of the
arguments of the 6j that is based on their classical and Regge symmetries, and
a detailed investigation of new geometrical aspects of the 6j symbols.
Specifically we compare the geometric recursion analysis of Schulten and Gordon
with the methods of this paper. The 1D recursion relation, written as a matrix
diagonalization problem, permits an interpretation as a discrete
Schr\"odinger-like equations and an asymptotic analysis illustrates
semiclassical and classical limits in terms of Hamiltonian evolution.Comment: 14 pages,9 figures, presented at ICCSA 2013 13th International
Conference on Computational Science and Applicatio
When does an individual accept misinformation? An extended investigation through cognitive modeling
Inflectional loci of scrolls
Let be a scroll over a smooth curve and let
\L=\mathcal O_{\mathbb P^N}(1)|_X denote the hyperplane bundle. The special
geometry of implies that some sheaves related to the principal part bundles
of \L are locally free. The inflectional loci of can be expressed in
terms of these sheaves, leading to explicit formulas for the cohomology classes
of the loci. The formulas imply that the only uninflected scrolls are the
balanced rational normal scrolls.Comment: 9 pages, improved version. Accepted in Mathematische Zeitschrif
Wild and Farmed Sea Bass (Dicentrarchus Labrax): Comparison of Biometry Traits, Chemical and Fatty Acid Composition of Fillets
Sea bass is a fish widely produced, consumed and appreciated in Italy. Its intensive rearing system provides the consumption of valuable fish to a wider population. Thanks to the use of an appropriate feed, it is possible to obtain reared sea bass which are richer in total lipid with a majority presence of polyunsaturated fatty acids, such as n-3 and n-6 series. In this study, a total of 75 specimens of European sea bass coming from three different origins (two farmed and one wild) were considered, with 25 fish from each origin. Biometry traits were valued as of the chemical and fatty acid profile of fillets. Biometric indices, proximate composition and fatty acid percentage were significantly affected by the rearing system. Fishes from the intensive rearing system (IRS) showed the highest value of relative profile and condition factor, a higher content of lipid and total n-6 that influenced the n-6/n-3 ratio and the atherogenic indexes, and values that indicated their flesh for human consumption as a healthy alternative to the wild fishes
Improving Interpretability and Regularization in Deep Learning
IEEE Deep learning approaches yield state-of-the-art performance in a range of tasks, including automatic speech recognition. However, the highly distributed representation in a deep neural network (DNN) or other network variations are difficult to analyse, making further parameter interpretation and regularisation challenging. This paper presents a regularisation scheme acting on the activation function output to improve the network interpretability and regularisation. The proposed approach, referred to as activation regularisation, encourages activation function outputs to satisfy a target pattern. By defining appropriate target patterns, different learning concepts can be imposed on the network. This method can aid network interpretability and also has the potential to reduce over-fitting. The scheme is evaluated on several continuous speech recognition tasks: the Wall Street Journal continuous speech recognition task, eight conversational telephone speech tasks from the IARPA Babel program and a U.S. English broadcast news task. On all the tasks, the activation regularisation achieved consistent performance gains over the standard DNN baselines
Physical-Mechanical Modifications of Eggs for Food-Processing During Storage
Abstract Physical-mechanical properties of egg constituents and their modifications during storage and poststorage greatly influence the efficiency of food processing, such as the separation of white and yolk by mechanical shelling. Thick albumen height, Haugh unit, yolk index and vitelline membrane-yolk system strength of eggs from Hy-Line White and Lohmann Brown hens were analyzed during 7 mo of storage at 0°C performing 3 poststorage treatments: i) immediately after refrigeration, T1; ii) after a further 6 h at 18°C after refrigeration, T2; and iii) after a week at 18°C after refrigeration, T3. For all qualitative parameters considered, this last poststorage treatment appeared to be the factor that produced the highest decrements; with respect to the first poststorage treatment, a further week at 18°C after refrigeration can involve mean decreases of about 19, 14, 14, and 16% in thick albumen height, Haugh unit, yolk index, and vitelline membrane-yolk system strength (in terms of maximum force), respectively. During about 7 mo of storage at 0°C, the latter parameter decreases, on average, by 10%. Increasing the storage time, physical-mechanical behavior was sometimes divergent from the observed trends
European wildcat populations are subdivided into five main biogeographic groups: consequences of Pleistocene climate changes or recent anthropogenic fragmentation?
Extant populations of the European wildcat are fragmented across the continent, the likely consequence of recent extirpations due to habitat loss and over-hunting. However, their underlying phylogeographic history has never been reconstructed. For testing the hypothesis that the European wildcat survived the Ice Age fragmented in Mediterranean refuges, we assayed the genetic variation at 31 microsatellites in 668 presumptive European wildcats sampled in 15 European countries. Moreover, to evaluate the extent of subspecies/population divergence and identify eventual wild × domestic cat hybrids, we genotyped 26 African wildcats from Sardinia and North Africa and 294 random-bred domestic cats. Results of multivariate analyses and Bayesian clustering confirmed that the European wild and the domestic cats (plus the African wildcats) belong to two well-differentiated clusters (average Ф ST = 0.159, r st = 0.392, P > 0.001; Analysis of molecular variance [AMOVA]). We identified from c. 5% to 10% cryptic hybrids in southern and central European populations. In contrast, wild-living cats in Hungary and Scotland showed deep signatures of genetic admixture and introgression with domestic cats. The European wildcats are subdivided into five main genetic clusters (average Ф ST = 0.103, r st = 0.143, P > 0.001; AMOVA) corresponding to five biogeographic groups, respectively, distributed in the Iberian Peninsula, central Europe, central Germany, Italian Peninsula and the island of Sicily, and in north-eastern Italy and northern Balkan regions (Dinaric Alps). Approximate Bayesian Computation simulations supported late Pleistocene-early Holocene population splittings (from c. 60 k to 10 k years ago), contemporary to the last Ice Age climatic changes. These results provide evidences for wildcat Mediterranean refuges in southwestern Europe, but the evolution history of eastern wildcat populations remains to be clarified. Historical genetic subdivisions suggest conservation strategies aimed at enhancing gene flow through the restoration of ecological corridors within each biogeographic units. Concomitantly, the risk of hybridization with free-ranging domestic cats along corridor edges should be carefully monitored
Morph-to-word transduction for accurate and efficient automatic speech recognition and keyword search
© 2017 IEEE. Word units are a popular choice in statistical language modelling. For inflective and agglutinative languages this choice may result in a high out of vocabulary rate. Subword units, such as morphs, provide an interesting alternative to words. These units can be derived in an unsupervised fashion and empirically show lower out of vocabulary rates. This paper proposes a morph-to-word transduction to convert morph sequences into word sequences. This enables powerful word language models to be applied. In addition, it is expected that techniques such as pruning, confusion network decoding, keyword search and many others may benefit from word rather than morph level decision making. However, word or morph systems alone may not achieve optimal performance in tasks such as keyword search so a combination is typically employed. This paper proposes a single index approach that enables word, morph and phone searches to be performed over a single morph index. Experiments are conducted on IARPA Babel program languages including the surprise languages of the OpenKWS 2015 and 2016 competitions
Imaging-based representation and stratification of intra-tumor heterogeneity via tree-edit distance
Personalized medicine is the future of medical practice. In oncology, tumor heterogeneity assessment represents a pivotal step for effective treatment planning and prognosis prediction. Despite new procedures for DNA sequencing and analysis, non-invasive methods for tumor characterization are needed to impact on daily routine. On purpose, imaging texture analysis is rapidly scaling, holding the promise to surrogate histopathological assessment of tumor lesions. In this work, we propose a tree-based representation strategy for describing intra-tumor heterogeneity of patients affected by metastatic cancer. We leverage radiomics information extracted from PET/CT imaging and we provide an exhaustive and easily readable summary of the disease spreading. We exploit this novel patient representation to perform cancer subtyping according to hierarchical clustering technique. To this purpose, a new heterogeneity-based distance between trees is defined and applied to a case study of prostate cancer. Clusters interpretation is explored in terms of concordance with severity status, tumor burden and biological characteristics. Results are promising, as the proposed method outperforms current literature approaches. Ultimately, the proposed method draws a general analysis framework that would allow to extract knowledge from daily acquired imaging data of patients and provide insights for effective treatment planning
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