Breaking the Architecture Barrier: A Method for Efficient Knowledge Transfer Across Networks

Transfer learning is a popular technique for improving the performance of neural networks. However, existing methods are limited to transferring parameters between networks with same architectures. We present a method for transferring parameters between neural networks with different architectures. Our method, called DPIAT, uses dynamic programming to match blocks and layers between architectures and transfer parameters efficiently. Compared to existing parameter prediction and random initialization methods, it significantly improves training efficiency and validation accuracy. In experiments on ImageNet, our method improved validation accuracy by an average of 1.6 times after 50 epochs of training. DPIAT allows both researchers and neural architecture search systems to modify trained networks and reuse knowledge, avoiding the need for retraining from scratch. We also introduce a network architecture similarity measure, enabling users to choose the best source network without any training.Comment: 23 pages, 16 figure

Nuclear Attenuation of high energy two-hadron system in the string model

Nuclear attenuation of the two-hadron system is considered in the string model. The two-scale model and its improved version with two different choices of constituent formation time and sets of parameters obtained earlier for the single hadron attenuation, are used to describe available experimental data for the $z$-dependence of subleading hadron, whereas satisfactory agreement with the experimental data has been observed. A model prediction for $\nu$-dependence of the nuclear attenuation of the two-hadron system is also presented.Comment: 8 page

Chaos Machine: Different Approach to the Application and Significance of Numbers

In this paper we describe a theoretical model of \underline{chaos machine}, which combines the benefits of hash function and pseudo-random function, forming flexible \textit{one-way} \underline{push-pull interface}. It presents the idea to create a universal tool (design pattern) with modular design and customizable parameters, that can be applied where \textit{randomness} and \textit{sensitiveness} is needed (random oracle), and where appropriate construction determines case of application and selection of parameters provides preferred properties and security level. Machine can be used to implement many cryptographic primitives, including cryptographic hashes, message authentication codes and pseudo-random number generators. Additionally, document includes sample implementation of chaos machine named Naive Czyzewski Generator, abbreviated NCG, that passes all the Dieharder, NIST and TestU01 test sets. Algorithm was designed and evaluated to be a cryptographically strong, inasmuch as indistinguishable from a uniform random function. The generator was developed to work as cryptographically secure pseudo-random number generator, collision resistance hash function or a cryptographic module. One can target a given period length by choosing the appropriate space parameter, i.e., for a given parameter $m$, algorithm is claimed to have period between $2^{8m}$ to $2^{16m}$

Hadron production in deep inelastic lepton-nucleus scattering

Predictions for semi-inclusive deep inelastic lepton-nucleus scattering are presented. Both the effects of gluon radiation by the struck quark and the absorption of the produced hadron are considered. The gluon radiation covers a larger window in virtuality $Q^2$ because of the increased deconfinement of quarks inside nuclei. The absorption of hadrons formed inside the nucleus is described with a flavor dependent cross section. Calculations for rescaled fragmentation functions and nuclear absorption are compared with the EMC and HERMES data for N, Cu and Kr targets with respect to the deuteron target. Predictions for Ne and Xe targets in the HERMES kinematic regime are given.Comment: 27 pages, 12 figures. Section 2 on rescaling modified. Extended discussion of the results in Sec. 5 and 6. To be published in Nucl.Phys.

The impact of pulsed electric field on the extraction of bioactive compounds from beetroot

Beetroot is a root vegetable rich in different bioactive components, such as vitamins, minerals, phenolics, carotenoids, nitrate, ascorbic acids, and betalains, that can have a positive effect on human health. The aim of this work was to study the influence of the pulsed electric field (PEF) at different electric field strengths (4.38 and 6.25 kV/cm), pulse number 10\u201330, and energy input 0\u201312.5 kJ/kg as a pretreatment method on the extraction of betalains from beetroot. The obtained results showed that the application of PEF pre-treatment significantly (p < 0.05) influenced the efficiency of extraction of bioactive compounds from beetroot. The highest increase in the content of betalain compounds in the red beet\u2019s extract (betanin by 329%, vulgaxanthin by 244%, compared to the control sample), was noted for 20 pulses of electric field at 4.38 kV/cm of strength. Treatment of the plant material with a PEF also resulted in an increase in the electrical conductivity compared to the non-treated sample due to the increase in cell membrane permeability, which was associated with leakage of substances able to conduct electricity, including mineral salts, into the intercellular space

A global reanalysis of nuclear parton distribution functions

We determine the nuclear modifications of parton distribution functions of bound protons at scales $Q^2\ge 1.69$ GeV$^2$ and momentum fractions $10^{-5}\le x\le 1$ in a global analysis which utilizes nuclear hard process data, sum rules and leading-order DGLAP scale evolution. The main improvements over our earlier work {\em EKS98} are the automated $\chi^2$ minimization, simplified and better controllable fit functions, and most importantly, the possibility for error estimates. The resulting 16-parameter fit to the N=514 datapoints is good, $\chi^2/{\rm d.o.f}=0.82$. Within the error estimates obtained, the old {\em EKS98} parametrization is found to be fully consistent with the present analysis, with no essential difference in terms of $\chi^2$ either. We also determine separate uncertainty bands for the nuclear gluon and sea quark modifications in the large-$x$ region where they are not stringently constrained by the available data. Comparison with other global analyses is shown and uncertainties demonstrated. Finally, we show that RHIC-BRAHMS data for inclusive hadron production in d+Au collisions lend support for a stronger gluon shadowing at $x<0.01$ and also that fairly large changes in the gluon modifications do not rapidly deteriorate the goodness of the overall fits, as long as the initial gluon modifications in the region $x\sim 0.02-0.04$ remain small.Comment: 33 pages, 14 figure

Atomic Mass Dependence of Hadron Production in Deep Inelastic Scattering on Nuclei

Hadron production in lepton-nucleus deep inelastic scattering is studied in an absorption model. In the proposed model, the early stage of hadronization in the nuclear medium is dominated by prehadron formation and absorption, controlled by flavor-dependent formation lengths and absorption cross sections. Computations for hadron multiplicity ratios are presented and compared with the HERMES experimental data for pions, kaons, protons and antiprotons. The mass-number dependence of hadron attenuation is shown to be sensitive to the underlying hadronization dynamics. Contrary to common expectations for absorption models, a leading term proportional to A^{2/3} is found. Deviations from the leading behavior arise at large mass-numbers and large hadron fractional momenta.Comment: 30 pages, 10 figures, v2: minor changes (legend in figs 5 & 6 is added), v3: additional explanations are added, v4: Version combines v3 and the erratum hep-ph/050803