Notes

Over- and also under-estimation regarding COVID-19 massive.
We find that the Schwinger boson mean field theory (SBMFT) supplemented with Gutzwiller projection provides an exceedingly accurate description for the ground state of the spin-12triangular lattice antiferromagnetic Heisenberg model (spin-12TLHAF). However, we find the SBMFT fails even qualitatively in the description of the dynamical behavior of the system. In particular, the SBMFT fails to predict the Goldstone mode in the magnetic ordered phase. We show that the coherent peak in the two-spinon continuum in the presence of spinon condensate should not be interpreted as a magnon mode. The SBMFT also predicts incorrectly a gapless longitudinal spin fluctuation mode in the magnetic ordered phase. We show that these failures are related to the following facts (1) spinon condensation fails to provide a consistent description of the order parameter manifold of the 120 degree ordered phase. (2) There lacks in the SBMFT the coupling between the uncondensed spinon and the spinon condensate, which breaks both the spin rotational and the translational symmetry. (3) There lacks in the SBMFT the rigidity that is related to the no double occupancy constraint on the spinon system. We show that such failures of the SBMFT is neither restricted to the spin-12TLHAF nor to the magnetic ordered phase. We proposed a generalized SBMFT to resolve the first two issues and a new formalism to address the third issue.Objective.Spike sorting is the process of extracting neuronal action potentials, or spikes, from an extracellular brain recording, and assigning each spike to its putative source neuron. Spike sorting is usually treated as a clustering problem. However, this clustering process is known to be affected by overlapping spikes. Existing methods for resolving spike overlap typically require an expensive post-processing of the clustering results. In this paper, we propose the design of a domain-specific feature map, which enables the resolution of spike overlap directly in the feature space.Approach.The proposed domain-specific feature map is based on a neural network architecture that is trained to simultaneously perform spike sorting and spike overlap resolution. Overlapping spikes clusters can be identified in the feature space through a linear relation with the single-neuron clusters for which the neurons contribute to the overlapping spikes. To aid the feature map training, a data augmentation procedure is presented that is based on biophysical simulations.Main results.We demonstrate the potential of our method on independent and realistic test data. We show that our novel approach for resolving spike overlap generalizes to unseen and realistic test data. Furthermore, the sorting performance of our method is shown to be similar to the state-of-the-art, but our method does not assume the availability of spike templates for resolving spike overlap.Significance.Resolving spike overlap directly in the feature space, results in an overall simplified spike sorting pipeline compared to the state-of-the-art. For the state-of-the-art, the overlapping spike snippets exhibit a large spread in the feature space and do not appear as concentrated clusters. This can lead to biased spike template estimates which affect the sorting performance of the state-of-the-art. In our proposed approach, overlapping spikes form concentrated clusters and spike overlap resolution does not depend on the availability of spike templates.The aim of the present work is to investigate the behavior of two diode-type detectors (PTW microDiamond 60019 and PTW microSilicon 60023) in transverse magnetic field under small field conditions. mTOR inhibitor therapy A formalism based on TRS 483 has been proposed serving as the framework for the application of these high-resolution detectors under these conditions. Measurements were performed at the National Metrology Institute of Germany (PTB, Braunschweig) using a research clinical linear accelerator facility. Quadratic fields corresponding to equivalent square field sizesSbetween 0.63 and 4.27 cm at the depth of measurement were used. The magnetic field strength was varied up to 1.4 T. Experimental results have been complemented with Monte Carlo simulations up to 1.5 T. Detailed simulations were performed to quantify the small field perturbation effects and the influence of detector components on the dose response. The does response of both detectors decreases by up to 10% at 1.5 T in the largest field size investigated. InS = 0.63 cm, this reduction at 1.5 T is only about half of that observed in field sizesS > 2 cm for both detectors. The results of the Monte Carlo simulations show agreement better than 1% for all investigated conditions. Due to normalization at the machine specific reference field, the resulting small field output correction factors for both detectors in magnetic fieldkQclin,QmsrBare smaller than those in the magnetic field-free case, where correction up to 6.2% at 1.5 T is required for the microSilicon in the smallest field size investigated. The volume-averaging effect of both detectors was shown to be nearly independent of the magnetic field. The influence of the enhanced-density components within the detectors has been identified as the major contributors to their behaviors in magnetic field. Nevertheless, the effect becomes weaker with decreasing field size that may be partially attributed to the deficiency of low energy secondary electrons originated from distant locations in small fields.Objective. This study examines how the geometrical arrangement of electrodes influences spike sorting efficiency, and attempts to formalise principles for the design of electrode systems enabling optimal spike sorting performance.Approach. The clustering performance of KlustaKwik, a popular toolbox, was evaluated using semi-artificial multi-channel data, generated from a library of real spike waveforms recorded in the CA1 region of mouse Hippocampusin vivo.Main results. Based on spike sorting results under various channel configurations and signal levels, a simple model was established to describe the efficiency of different electrode geometries. Model parameters can be inferred from existing spike waveform recordings, which allowed quantifying both the cooperative effect between channels and the noise dependence of clustering performance.Significance. Based on the model, analytical and numerical results can be derived for the optimal spacing and arrangement of electrodes for one- and two-dimensional electrode systems, targeting specific brain areas.
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