Magnetic systems at criticality: different signatures of scaling

Different aspects of critical behaviour of magnetic materials are presented and discussed. The scaling ideas are shown to arise in the context of purely magnetic properties as well as in that of thermal properties as demonstrated by magnetocaloric effect or combined scaling of excess entropy and order parameter. Two non-standard approaches to scaling phenomena are described. The presented concepts are exemplified by experimental data gathered on four representatives of molecular magnets.Comment: 33 pages, 16 figure

Quantum phase transitions in alternating spin-(1/2, 5/2) Heisenberg chains

The ground state spin-wave excitations and thermodynamic properties of two types of ferrimagnetic chains are investigated: the alternating spin-1/2 spin-5/2 chain and a similar chain with a spin-1/2 pendant attached to the spin-5/2 site. Results for magnetic susceptibility, magnetization and specific heat are obtained through the finite-temperature Lanczos method with the aim in describing available experimental data, as well as comparison with theoretical results from the semiclassical approximation and the low-temperature susceptibility expansion derived from Takahashi's modified spin-wave theory. In particular, we study in detail the temperature vs. magnetic field phase diagram of the spin-1/2 spin-5/2 chain, in which several low-temperature quantum phases are identified: the Luttinger Liquid phase, the ferrimagnetic plateau and the fully polarized one, and the respective quantum critical points and crossover lines

Adenovirus E1A directly targets the E2F/DP-1 complex

Deregulation of the cell cycle is of paramount importance during adenovirus infection. Adenovirus normally infects quiescent cells and must initiate the cell cycle in order to propagate itself. The pRb family of proteins controls entry into the cell cycle by interacting with and repressing transcriptional activation by the E2F transcription factors. The viral E1A proteins indirectly activate E2F-dependent transcription and cell cycle entry, in part, by interacting with pRb and family members to free the E2Fs. We report here that an E1A 13S isoform can unexpectedly activate E2F-responsive gene expression independently of binding to the pRb family of proteins. We demonstrate that E1A binds to E2F/DP-1 complexes through a direct interaction with DP-1. E1A appears to utilize this binding to recruit itself to E2F-regulated promoters, and this allows the E1A 13S protein, but not the E1A 12S protein, to activate transcription independently of interaction with pRb. Importantly, expression of E1A 13S, but not E1A 12S, led to significant enhancement of E2F4 occupancy of E2F sites of two E2F-regulated promoters. These observations identify a novel mechanism by which adenovirus deregulates the cell cycle and suggest that E1A 13S may selectively activate a subset of E2F-regulated cellular genes during infection. © 2011, American Society for Microbiology

Observation of inhibited electron-ion coupling in strongly heated graphite

Creating non-equilibrium states of matter with highly unequal electron and lattice temperatures (Tele≠Tion) allows unsurpassed insight into the dynamic coupling between electrons and ions through time-resolved energy relaxation measurements. Recent studies on low-temperature laser-heated graphite suggest a complex energy exchange when compared to other materials. To avoid problems related to surface preparation, crystal quality and poor understanding of the energy deposition and transport mechanisms, we apply a different energy deposition mechanism, via laser-accelerated protons, to isochorically and non-radiatively heat macroscopic graphite samples up to temperatures close to the melting threshold. Using time-resolved x ray diffraction, we show clear evidence of a very small electron-ion energy transfer, yielding approximately three times longer relaxation times than previously reported. This is indicative of the existence of an energy transfer bottleneck in non-equilibrium warm dense matter

Overview of the ImageCLEFmed 2020 Concept Prediction Task: Medical Image Understanding

This paper describes the ImageCLEFmed 2020 Concept Detection Task. After first being proposed at ImageCLEF 2017, the medical task is in its 4th edition this year, as the automatic detection from medical images still remains a challenging task. In 2020, the format remained the same as in 2019, with a single sub-task. The concept detection task is part of the medical tasks, alongside the tuberculosis and visual question and answering tasks. Similar to the 2019 edition, the data set focuses on radiology images rather than biomedical images, however with an increased number of images. The distributed images were extracted from the biomedical open access literature (PubMed Central). The development data consists of 65,753 training and 15,970 validation images. Each image has corresponding Unified Medical Language System (UMLS™) concepts, that were extracted from the original article image captions. In this edition, additional imaging acquisition technique labels were included in the distributed data, which were adopted for pre-filtering steps, concept selection and ensemble algorithms. Most applied approaches for the automatic detection of concepts were deep learning based architectures. Long short-term memory (LSTM) recurrent neural networks (RNN), adversarial auto-encoder, convolutional neural networks (CNN) image encoders and transfer learning-based multi-label classification models were adopted. The performances of the submitted models (best score 0.3940) were evaluated using F1-scores computed per image and averaged across all 3,534 test images