Computer analysis of EEG data for a normative library Final report, Sep. 24, 1963 - Jan. 31, 1966

Computer analysis of electroencephalographic data for development of normative criteri

Duality Between the Weak and Strong Interaction Limits for Randomly Interacting Fermions

We establish the existence of a duality transformation for generic models of interacting fermions with two-body interactions. The eigenstates at weak and strong interaction U possess similar statistical properties when expressed in the U=0 and U=infinity eigenstates bases respectively. This implies the existence of a duality point U_d where the eigenstates have the same spreading in both bases. U_d is surrounded by an interval of finite width which is characterized by a non Lorentzian spreading of the strength function in both bases. Scaling arguments predict the survival of this intermediate regime as the number of particles is increased.Comment: RevTex4, 4 pages, 4 figures. Accepted for publication at Phys. Rev. Let

Memory Aware Synapses: Learning what (not) to forget

Humans can learn in a continuous manner. Old rarely utilized knowledge can be overwritten by new incoming information while important, frequently used knowledge is prevented from being erased. In artificial learning systems, lifelong learning so far has focused mainly on accumulating knowledge over tasks and overcoming catastrophic forgetting. In this paper, we argue that, given the limited model capacity and the unlimited new information to be learned, knowledge has to be preserved or erased selectively. Inspired by neuroplasticity, we propose a novel approach for lifelong learning, coined Memory Aware Synapses (MAS). It computes the importance of the parameters of a neural network in an unsupervised and online manner. Given a new sample which is fed to the network, MAS accumulates an importance measure for each parameter of the network, based on how sensitive the predicted output function is to a change in this parameter. When learning a new task, changes to important parameters can then be penalized, effectively preventing important knowledge related to previous tasks from being overwritten. Further, we show an interesting connection between a local version of our method and Hebb's rule,which is a model for the learning process in the brain. We test our method on a sequence of object recognition tasks and on the challenging problem of learning an embedding for predicting $$ triplets. We show state-of-the-art performance and, for the first time, the ability to adapt the importance of the parameters based on unlabeled data towards what the network needs (not) to forget, which may vary depending on test conditions.Comment: ECCV 201

Modelling Winter Grass Growth and Senescence

In temperate climates, because net grass growth in winter is low, most grass growth models deal with the main growing season (Mar-Oct in the N Hemisphere), with little emphasis on grass growth in winter (Nov-Feb). However, grass tissue turns over continuously (Hennessy et al., 2004) and the fate of herbage entering the winter is important in extended grazing season systems. This study aimed to model winter grass growth for the period 15 Oct 2001 to 28 Jan 2002 for a range of autumn closing dates (1 Sep, 20 Sep and 10 Oct) by modifying an existing model, so that the amount of green leaf could be predicted at intervals over the winter

Random matrix analysis of complex networks

We study complex networks under random matrix theory (RMT) framework. Using nearest-neighbor and next-nearest-neighbor spacing distributions we analyze the eigenvalues of adjacency matrix of various model networks, namely, random, scale-free and small-world networks. These distributions follow Gaussian orthogonal ensemble statistic of RMT. To probe long-range correlations in the eigenvalues we study spectral rigidity via $\Delta_3$ statistic of RMT as well. It follows RMT prediction of linear behavior in semi-logarithmic scale with slope being $\sim 1/\pi^2$. Random and scale-free networks follow RMT prediction for very large scale. Small-world network follows it for sufficiently large scale, but much less than the random and scale-free networks.Comment: accepted in Phys. Rev. E (replaced with the final version

Suppression of Ground-State Magnetization in Finite-Sized Systems Due to Off-Diagonal Interaction Fluctuations

We study a generic model of interacting fermions in a finite-sized disordered system. We show that the off-diagonal interaction matrix elements induce density of states fluctuations which generically favor a minimum spin ground state at large interaction amplitude, $U$. This effect competes with the exchange effect which favors large magnetization at large $U$, and it suppresses this exchange magnetization in a large parameter range. When off-diagonal fluctuations dominate, the model predicts a spin gap which is larger for odd-spin ground states as for even-spin, suggesting a simple experimental signature of this off-diagonal effect in Coulomb blockade transport measurements.Comment: Final, substantially modified version of the article. Accepted for publication in Physical Review Letter

Interactions and Disorder in Quantum Dots: Instabilities and Phase Transitions

Using a fermionic renormalization group approach we analyse a model where the electrons diffusing on a quantum dot interact via Fermi-liquid interactions. Describing the single-particle states by Random Matrix Theory, we find that interactions can induce phase transitions (or crossovers for finite systems) to regimes where fluctuations and collective effects dominate at low energies. Implications for experiments and numerical work on quantum dots are discussed.Comment: 4 pages, 1 figure; version to appear in Phys Rev Letter

Generalized seniority from random Hamiltonians

We investigate the generic pairing properties of shell-model many-body Hamiltonians drawn from ensembles of random two-body matrix elements. Many features of pairing that are commonly attributed to the interaction are in fact seen in a large part of the ensemble space. Not only do the spectra show evidence of pairing with favored J=0 ground states and an energy gap, but the relationship between ground state wave functions of neighboring nuclei show signatures of pairing as well. Matrix elements of pair creation/annihilation operators between ground states tend to be strongly enhanced. Furthermore, the same or similar pair operators connect several ground states along an isotopic chain. This algebraic structure is reminiscent of the generalized seniority model. Thus pairing may be encoded to a certain extent in the Fock space connectivity of the interacting shell model even without specific features of the interaction required.Comment: 10 pages, 7 figure

Low value of detection of KRAS2 mutations in circulating DNA to differentiate chronic pancreatitis to pancreatic cancer

We read with great interest the article by Maire et al (2002), who evaluate the K-Ras mutations in circulating DNA to differentiate pancreatic cancer from chronic pancreatitis. Based on this, we also analysed KRAS2 mutations in the serum of 30 patients with pancreatic cancer and 40 patients with chronic pancreatitis. Pancreatic cancer patients were staged by means of dynamic computed tomography, magnetic resonance imaging, and angiography and/or endoscopic ultrasonography. Diagnosis was histologically confirmed for the patients who underwent surgery. The diagnosis of chronic pancreatitis was based on the radiologic data obtained by means of either endoscopic retrograde cholangiopancreatography or computed tomography. DNA was extracted from 20 ml of the serum by using the QIAmp Blood Kit (Qiagen) and the mutations in codon 12 of the K-ras gene were searched as described previously (Jiang et al, 1989). As positive controls, we used DNA from neoplastic tissues of 10 patients with pancreatic carcinoma by using the DNeasy Tissue Kit (Qiagen). For molecular analysis, DNA was amplified in the codon 12 region introducing a restriction site (GACCT) for digestion with BstNl restriction enzyme (PCR-RFLP). DNA from peripheral blood resulted not mutated in the 40 patients with chronic pancreatitis and in the 30 with pancreatic carcinoma, while DNA from pancreatic neoplastic tissue resulted mutated in 70% of the samples. To verify our results, all the samples were analysed by direct sequencing using Big Dye terminator v 1.1 cycle sequencing Kit and performing runs on ABI Prism 310 genetic analyzer (Applied Biosystem) Despite what was mentioned in Maire's article, we failed to find any mutations in all patients analysed, as well as we failed to correlate K-ras mutations with the levels of tumour markers such as Ca 19.9, CA242, CA50, CEA. The results of the present investigation lead us to these conclusions: (1) the eventual presence of cancer cells in peripheral blood may be a rare event, even if numerous reports support the detection of K-ras abnormalities in the serum, (2) neoplastic cells are supposed to circulate in clusters, and consequently their cognition could be hampered by a single blood sample extraction. (3) Large amounts of nonmutated DNA, coming from leucocytes held in the buffy coat layer, might also mask some vestiges of the mutant type of K-ras gene

Chaos Thresholds in finite Fermi systems

The development of Quantum Chaos in finite interacting Fermi systems is considered. At sufficiently high excitation energy the direct two-particle interaction may mix into an eigen-state the exponentially large number of simple Slater-determinant states. Nevertheless, the transition from Poisson to Wigner-Dyson statistics of energy levels is governed by the effective high order interaction between states very distant in the Fock space. The concrete form of the transition depends on the way one chooses to work out the problem of factorial divergency of the number of Feynman diagrams. In the proposed scheme the change of statistics has a form of narrow phase transition and may happen even below the direct interaction threshold.Comment: 9 pages, REVTEX, 2 eps figures. Enlarged versio