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Recent data give unexpectedly large cross-sections for charmed particle production at high xF in hadron collisions. This may imply that the proton has a non-negligible uudcc Fock component. The interesting consequences of such a hypothesis are explored.
We consider hadron production in deep inelastic scattering of electrons on photons. 1. (i)Exploiting the leading order QCD corrections due to gluon bremsstrahlung we find that the photon structure functions rapidly approach their asymptotic form which can be calculated in QCD. 2. (ii)Replacing QCD by a theory with a fixed quark-gluon coupling constant (scalar or abelian gluons) gives dramatic chan
We study deep inelastic scattering of an electron or positron on an almost real photon target in the reaction e+e− → e+e− + hadrons with C = +, where one e+ or e− is scattered at small or zero angle, yielding a virtual photon γ(k), k2 ∼ O(−me2). The other e− or e+ scatters on this virtual photon, emerging at large angle. We emphasize particularly: (i) the pointlike QCD contribution to the structur
We present a simple physical model of a nonperturbative gluon jet. The gluon fragments into isoscalar clusters in a cascade fashion. The primary mesons produced are η, η′, ω, φ (and states of bound glue). The experimental consequences of the model are dramatic, allowing a clear test.
The origin of the observed scaling violations in inclusive e+e- annihilation is investigated. Perturbative jet evolution is not necessarily the only reason for scale breaking in the hadron spectra at present energies. Remnants of finite-transverse-momentum and mass effects are still important in nonperturbative, cascade-type, jet formation in the 10 GeV range. Heavy-quark fragmentation has a stron
Recent advances in coarse-grained lattice and off-lattice protein models are reviewed. The sequence dependence of thermodynamical folding properties are investigated and evidence for non-randomness of the binary sequences of good folders are discussed. Similar patterns for non-randomness are found for real proteins. Dynamical parameter MC methods, such as the tempering and multisequence algorithms
A neural network algorithm for finding tracks in high energy physics experiments is presented. The performance of the algorithm is explored on modest size samples with encouraging results. It is inherently parallel and thus suitable for execution on a conventional SIMD architecture. More important, it naturally lends itself to direct implementations in custom made hardware, which would permit real
An F77 package for feed-forward artificial neural network data processing, JETNET 3.0, is presented. It represents a substantial extension and generalization of an earlier release, JETNET 2.0. The package, which consists of a set of subroutines, is focused on multilayer perceptron architectures. As compared to earlier versions it contains a variety of minimization options, measures for monitoring
A neural network method for identifying the ancestor of a hadron jet is presented. The idea is to find an efficient mapping between certain observed hadronic kinematical variables and the quark-gluon identity. This is done with a neuronic expansion in terms of a network of sigmoidal functions using a gradient descent procedure, where the errors are back-propagated through the network. With this me
The mean field theory (MFT) learning algorithm is elaborated and explored with respect to a variety of tasks. MFT is benchmarked against the back-propagation learning algorithm (BP) on two different feature recognition problems: two-dimensional mirror symmetry and multidimensional statistical pattern classification. We find that while the two algorithms are very similar with respect to generalizat
A F77 package of adaptive artificial neural network algorithms, JETNET 2.0, is presented. Its primary target is the high energy physics community, but it is general enough to be used in any pattern-recognition application area. The basic ingredients are the multilayer perceptron back-propagation algorithm and the topological self-organizing map. The package consists of a set of subroutines, which
Self-organizing neural networks are briefly reviewed and compared with supervised learning algorithms like back-propagation. The power of self-organization networks is in their capability of displaying typical features in a transparent manner. This is successfully demonstrated with two applications from hadronic jet physics; hadronization model discrimination and separation of b, c and light quark
The use of diafiltration as part of ultrafiltration processes on an industrial scale is now the state-of-the-art in the food & beverage, biotech and pharma industry for the recovery of fermentation broth. In this paper the advantages and disadvantages of the most common process modes of diafiltration - batch and continuous - will be discussed. Further, the new concept of counter-current diaf
In the food & beverage, biotech and pharma industry the use of ultrafiltration to recover fermentation broth is the state-of-the-art. These Ultrafiltration systems consist commonly of three stages: (1) pre-concentration stage, (2) diafiltration, and (3) final concentration. The process mode can be either batch or continuous. In the batch processes for all stages of the concentration the sam
Searches for dijet resonances with sub-TeV masses using the ATLAS detector at the Large Hadron Collider can be statistically limited by the bandwidth available to inclusive single-jet triggers, whose data-collection rates at low transverse momentum are much lower than the rate from standard model multijet production. This Letter describes a new search for dijet resonances where this limitation is
