Electronic correlations in FeGa3 and the effect of hole doping on its magnetic properties

We investigate signatures of electronic correlations in the narrow-gap semiconductor FeGa 3 by means of electrical resistivity and thermodynamic measurements performed on single crystals of FeGa 3 , Fe 1−x Mn x Ga 3 , and FeGa 3−y Zn y , complemented by a study of the 4d analog material RuGa 3 . We find that the inclusion of sizable amounts of Mn and Zn dopants into FeGa 3 does not induce an insulator-to-metal transition. Our study indicates that both substitution of Zn onto the Ga site and replacement of Fe by Mn introduces states into the semiconducting gap that remain localized even at highest doping levels. Most importantly, using neutron powder diffraction measurements, we establish that FeGa 3 orders magnetically above room temperature in a complex structure, which is almost unaffected by the doping with Mn and Zn. Using realistic many-body calculations within the framework of dynamical mean field theory (DMFT), we argue that while the iron atoms in FeGa 3 are dominantly in an S=1 state, there are strong charge and spin fluctuations on short-time scales, which are independent of temperature. Further, the low magnitude of local contributions to the spin susceptibility advocates an itinerant mechanism for the spin response in FeGa 3 . Our joint experimental and theoretical investigations classify FeGa 3 as a correlated band insulator with only small dynamical correlation effects, in which nonlocal exchange interactions are responsible for the spin gap of 0.4 eV and the antiferromagnetic order. We show that hole doping of FeGa 3 leads, within DMFT, to a notable strengthening of many-body renormalizations

Ground state of the spin-1/2 Heisenberg antiferromagnet on an Archimedean 4-6-12 lattice

An investigation of the N\'eel Long Range Order (NLRO) in the ground state of antiferromagnetic Heisenberg spin system on the two-dimensional, uniform, bipartite lattice consisting of squares, hexagons and dodecagons is presented. Basing on the analysis of the order parameter and the long-distance correlation function the NLRO is shown to occur in this system. Exact diagonalization and variational (Resonating Valence Bond) methods are applied.Comment: 4 pages, 6 figure

Potassium channels in cell cycle and cell proliferation

Normal cell-cycle progression is a crucial task for every multicellular organism, as it determines body size and shape, tissue renewal and senescence, and is also crucial for reproduction. On the other hand, dysregulation of the cell-cycle progression leading to uncontrolled cell proliferation is the hallmark of cancer. Therefore, it is not surprising that it is a tightly regulated process, with multifaceted and very complex control mechanisms. It is now well established that one of those mechanisms relies on ion channels, and in many cases specifically on potassium channels. Here, we summarize the possible mechanisms underlying the importance of potassium channels in cell-cycle control and briefly review some of the identified channels that illustrate the multiple ways in which this group of proteins can influence cell proliferation and modulate cell-cycle progression

Attentive Group Equivariant Convolutional Networks

Although group convolutional networks are able to learn powerful representations based on symmetry patterns, they lack explicit means to learn meaningful relationships among them (e.g., relative positions and poses). In this paper, we present attentive group equivariant convolutions, a generalization of the group convolution, in which attention is applied during the course of convolution to accentuate meaningful symmetry combinations and suppress non-plausible, misleading ones. We indicate that prior work on visual attention can be described as special cases of our proposed framework and show empirically that our attentive group equivariant convolutional networks consistently outperform conventional group convolutional networks on benchmark image datasets. Simultaneously, we provide interpretability to the learned concepts through the visualization of equivariant attention maps.Comment: Proceedings of the 37th International Conference on Machine Learning (ICML), 202

Generalized Paraxial Ray Trace Procedure Derived from Geodesic Deviation

Paraxial ray tracing procedures have become widely accepted techniques for acoustic models in seismology and underwater acoustics. To date a generic form of these procedures including fluid motion and time dependence has not appeared in the literature. A detailed investigation of the characteristic curves of the equations of hydrodynamics allows for an immediate generalization of the procedure to be extracted from the equation form geodesic deviation. The general paraxial ray trace equations serve as an ideal supplement to ordinary ray tracing in predicting the deformation of acoustic beams in random environments. The general procedure is derived in terms of affine parameterization and in a coordinate time parameterization ideal for application to physical acoustic ray propagation. The formalism is applied to layered media, where the deviation equation reduces to a second order differential equation for a single field with a general solution in terms of a depth integral along the ray path. Some features are illustrated through special cases which lead to exact solutions in terms of either ordinary or special functions.Comment: Original; 40 pages (double spaced), 1 figure Replaced version; 36 pages single spaced, 7 figures. Expanded content; Complete derivation of the equations from the equations of hydrodynamics, introduction of an auxiliary basis for three dimensional wave-front modeling. Typos in text and equations correcte

Downfolded Self-Energy of Many-Electron Systems

Starting from the full many-body Hamiltonian of interacting electrons the effective self-energy acting on electrons residing in a subspace of the full Hilbert space is derived. This subspace may correspond to, for example, partially filled narrow bands, which often characterize strongly correlated materials. The formalism delivers naturally the frequency-dependent effective interaction (the Hubbard U) and provides a general framework for constructing theoretical models based on the Green function language. It also furnishes a general scheme for first-principles calculations of complex systems in which the main correlation effects are concentrated on a small subspace of the full Hilbert space.Comment: 5 page

173. Does the correlation between chemotherapy-induced leukopenia with response in locally advanced breast cancer exist?

PurposeThe correlation between chemotherapy-induced toxicity and treatment outcome in cancer patients has not been thoroughly studied. Our aim was to evaluate whether leukopenia following primary chemotherapy may be predictive for response in patients with locally advanced breast cancer.Patients and MethodsThe records of 164 breast cancer patients administered primary chemotherapy between 1985 and 1995 were analysed. Most of the patients presented with locally advanced disease, however included were also patients with large operable tumours. Chemotherapy included one of the three combinations: CMF; modified Cooper regimen (CMFVP); 31 patients (19%), anthracycline-based regimens (FAC and FEC); 16 patients (10%) and 118 patients (71%).ResultsThe objective response rate in the entire group was 58%; 75% in patients who developed grade 2–3 leukopenia during induction chemotherapy, and 52% in those who had no or grade 1 leukopenia (p < 0.01, multivariate analysis). No other patient- or treatment-related factor including age, performance status, T stage, N stage, supraclavicular Iymph node involvement, inflammatory carcinoma or chemotherapy regimen correlated with response to chemotherapy. There was no correlation between treatment-induced leukopenia and overall survival.ConclusionsThese findings suggest a relationship between chemotherapy induced leukopenia and tumour response in patients with locally advanced breast cancer. The prognostic impact of leukopenia is negliglble