Generating dynamic higher-order Markov models in web usage mining

Markov models have been widely used for modelling users’ web navigation behaviour. In previous work we have presented a dynamic clustering-based Markov model that accurately represents second-order transition probabilities given by a collection of navigation sessions. Herein, we propose a generalisation of the method that takes into account higher-order conditional probabilities. The method makes use of the state cloning concept together with a clustering technique to separate the navigation paths that reveal differences in the conditional probabilities. We report on experiments conducted with three real world data sets. The results show that some pages require a long history to understand the users choice of link, while others require only a short history. We also show that the number of additional states induced by the method can be controlled through a probability threshold parameter

Electroweak Phase Transitions in left-right symmetric models

We study the finite-temperature effective potential of minimal left-right symmetric models containing a bidoublet and two triplets in the scalar sector. We perform a numerical analysis of the parameter space compatible with the requirement that baryon asymmetry is not washed out by sphaleron processes after the electroweak phase transition. We find that the spectrum of scalar particles for these acceptable cases is consistent with present experimental bounds.Comment: 20 pages, 5 figures (included), some comments added, typos corrected and new references included. Final version to appear in PR

New measurement of the rare decay ϕ→η′γ\phi \to \eta' \gamma with CMD-2

A new measurement of the rare decay \phi \to \eta' \gamma performed with the CMD-2 detector at Novosibirsk is described. Of the data sample corresponding to the integrated luminosity of 14.5 pb^{-1}, twenty one events have been selected in the mode \eta'\to\pi^+\pi^-\eta, \eta\to\gamma\gamma. The following branching ratio was obtained: B(\phi \to \eta' \gamma) = (8.2^{+2.1}_{-1.9} \pm 1.1) 10^{-5}.Comment: 12 pages, 4 figures, LaTe

Activity-dependent degeneration of axotomized neuromuscular synapses in Wld(S) mice

AbstractActivity and disuse of synapses are thought to influence progression of several neurodegenerative diseases in which synaptic degeneration is an early sign. Here we tested whether stimulation or disuse renders neuromuscular synapses more or less vulnerable to degeneration, using axotomy as a robust trigger. We took advantage of the slow synaptic degeneration phenotype of axotomized neuromuscular junctions in flexor digitorum brevis (FDB) and deep lumbrical (DL) muscles of Wallerian degeneration-Slow (WldS) mutant mice. First, we maintained ex vivo FDB and DL nerve-muscle explants at 32°C for up to 48h. About 90% of fibers from WldS mice remained innervated, compared with about 36% in wild-type muscles at the 24-h checkpoint. Periodic high-frequency nerve stimulation (100Hz: 1s/100s) reduced synaptic protection in WldS preparations by about 50%. This effect was abolished in reduced Ca2+ solutions. Next, we assayed FDB and DL innervation after 7days of complete tetrodotoxin (TTX)-block of sciatic nerve conduction in vivo, followed by tibial nerve axotomy. Five days later, only about 9% of motor endplates remained innervated in the paralyzed muscles, compared with about 50% in 5day-axotomized muscles from saline-control-treated WldS mice with no conditioning nerve block. Finally, we gave mice access to running wheels for up to 4weeks prior to axotomy. Surprisingly, exercising WldS mice ad libitum for 4weeks increased about twofold the amount of subsequent axotomy-induced synaptic degeneration. Together, the data suggest that vulnerability of mature neuromuscular synapses to axotomy, a potent neurodegenerative trigger, may be enhanced bimodally, either by disuse or by hyperactivity

Artificial Intelligence for the Electron Ion Collider (AI4EIC)

The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028. This is an opportune time for artificial intelligence (AI) to be included from the start at this facility and in all phases that lead up to the experiments. The second annual workshop organized by the AI4EIC working group, which recently took place, centered on exploring all current and prospective application areas of AI for the EIC. This workshop is not only beneficial for the EIC, but also provides valuable insights for the newly established ePIC collaboration at EIC. This paper summarizes the different activities and R and D projects covered across the sessions of the workshop and provides an overview of the goals, approaches and strategies regarding AI/ML in the EIC community, as well as cutting-edge techniques currently studied in other experiments

Artificial Intelligence for the Electron Ion Collider (AI4EIC)

The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028. This is an opportune time for artificial intelligence (AI) to be included from the start at this facility and in all phases that lead up to the experiments. The second annual workshop organized by the AI4EIC working group, which recently took place, centered on exploring all current and prospective application areas of AI for the EIC. This workshop is not only beneficial for the EIC, but also provides valuable insights for the newly established ePIC collaboration at EIC. This paper summarizes the different activities and R and D projects covered across the sessions of the workshop and provides an overview of the goals, approaches and strategies regarding AI/ML in the EIC community, as well as cutting-edge techniques currently studied in other experiments