The Necessity of the Good Person Prosecutor

In a 2001 essay, Professor Abbe Smith asked the question whether a good person—i.e., a person who is committed to social justice—can be a good prosecutor. Although she acknowledged some hope that the answer to her question could be “yes,” Professor Smith concluded that the answer then was “no”—in part because she saw individual prosecutors generally as having very little discretion to “temper the harsh reality of the criminal justice system.” In this Online Symposium revisiting Professor Smith’s question seventeen years later, my answer to her question is “yes”—a good person can be a good prosecutor

Robust massive MIMO Equilization for mmWave systems with low resolution ADCs

Leveraging the available millimeter wave spectrum will be important for 5G. In this work, we investigate the performance of digital beamforming with low resolution ADCs based on link level simulations including channel estimation, MIMO equalization and channel decoding. We consider the recently agreed 3GPP NR type 1 OFDM reference signals. The comparison shows sequential DCD outperforms MMSE-based MIMO equalization both in terms of detection performance and complexity. We also show that the DCD based algorithm is more robust to channel estimation errors. In contrast to the common believe we also show that the complexity of MMSE equalization for a massive MIMO system is not dominated by the matrix inversion but by the computation of the Gram matrix.Comment: submitted to WCNC 2018 Workshop

Automated optimization of a reduced layer 5 pyramidal cell model based on experimental data.

The construction of compartmental models of neurons involves tuning a set of parameters to make the model neuron behave as realistically as possible. While the parameter space of single-compartment models or other simple models can be exhaustively searched, the introduction of dendritic geometry causes the number of parameters to balloon. As parameter tuning is a daunting and time-consuming task when performed manually, reliable methods for automatically optimizing compartmental models are desperately needed, as only optimized models can capture the behavior of real neurons. Here we present a three-step strategy to automatically build reduced models of layer 5 pyramidal neurons that closely reproduce experimental data. First, we reduce the pattern of dendritic branches of a detailed model to a set of equivalent primary dendrites. Second, the ion channel densities are estimated using a multi-objective optimization strategy to fit the voltage trace recorded under two conditions - with and without the apical dendrite occluded by pinching. Finally, we tune dendritic calcium channel parameters to model the initiation of dendritic calcium spikes and the coupling between soma and dendrite. More generally, this new method can be applied to construct families of models of different neuron types, with applications ranging from the study of information processing in single neurons to realistic simulations of large-scale network dynamics

Cloudphysical Parameters in Dependence on Height above Cloud Base in Different Clouds.

On flights with the DLR icing research aircraft the dependence of aircraft icing on cloudphysical parameters was determined; both for aircraft-referred icing and for normalized icing, as well as for various clouds and locations in clouds. This is done with an improvement of icing predicitons in mind. The species of the cloud and the distance from cloud base are called here cloud parameters; while under cloudphysical parameters are understood liquid water content, temperature, particle size distribution and particle phase. Results from four icing flights are discussed, selected from a total of forty vertical soundings. —The results are arranged in four classes: Stratus/cumulus mixed, stratus; with and without precipitation at the ground