Nanoporous GaN by UV assisted electroless etching for sensor applications

GaN-based devices have demonstrated excellent performance for electronics and optoelectronics applications. In particular, these devices exhibit very good performance when operated at high temperatures and in harsh environments when compared to similar devices fabricated with conventional material systems. The good stability, durability and biocompatibility of the nitrides have also led to the development of GaN based chemical and biological gas sensors. These devices have been developed using Schottky diodes with platinum or palladium contacts on GaN and AlGaN/GaN structures [1-3] and showed high sensitivity. However, the response may be further improved if the effective surface área is increased, allowing a more efficient accumulation of the gas induced dipole layer [4]. In this paper fabrication and characterization of nanoporous GaN is presented as a fírst step for the fabrication of improved GaN gas sensors

Bichromatic phase-control of interfering Autler-Townes spectra

We propose a new scheme to control the shape of the Autler-Townes (AT) doublet in the photoelectron spectrum from atomic resonance-enhanced multiphoton ionization (REMPI). The scheme is based on the interference of two AT doublets created by ionization of the strongly driven atom from the ground and the resonantly excited state using tailored bichromatic femtosecond (fs) laser pulses. In this scheme, the quantum phase of the photoelectrons is crucial for the manipulation of the AT doublet. The laser polarization state and the relative optical phase between the two colors are used to manipulate the interference pattern. We develop an analytical model to describe the bichromatic REMPI process and provide a physical picture of the control mechanism. To validate the model, the results are compared to an ab initio calculation based on the solution of the 2D time-dependent Schr\"odinger equation for the non-perturbative interaction of an atom with intense polarization-shaped bichromatic fs-laser pulses. Our results indicate that the control mechanism is robust with respect to the laser intensity facilitating its experimental observation.Comment: 13 pages, 5 figure

Screening of the quantum-confined Stark effect in AlN/GaN nanowire superlattices by Germanium doping

We report on electrostatic screening of polarization-induced internal electric fields in AlN/GaN nanowire heterostructures with Germanium-doped GaN nanodiscs embedded between AlN barriers. The incorporation of Germanium at concentrations above $10^{20}\,\text{cm}^{-3}$ shifts the photoluminescence emission energy of GaN nanodiscs to higher energies accompanied by a decrease of the photoluminescence decay time. At the same time, the thickness-dependent shift in emission energy is significantly reduced. In spite of the high donor concentration a degradation of the photoluminescence properties is not observed.Comment: Manuscript including Supplemental material (15 pages, 5 figures

Predictive Uncertainty-based Bias Mitigation in Ranking

Societal biases that are contained in retrieved documents have received increased interest. Such biases, which are often prevalent in the training data and learned by the model, can cause societal harms, by misrepresenting certain groups, and by enforcing stereotypes. Mitigating such biases demands algorithms that balance the trade-off between maximized utility for the user with fairness objectives, which incentivize unbiased rankings. Prior work on bias mitigation often assumes that ranking scores, which correspond to the utility that a document holds for a user, can be accurately determined. In reality, there is always a degree of uncertainty in the estimate of expected document utility. This uncertainty can be approximated by viewing ranking models through a Bayesian perspective, where the standard deterministic score becomes a distribution. In this work, we investigate whether uncertainty estimates can be used to decrease the amount of bias in the ranked results, while minimizing loss in measured utility. We introduce a simple method that uses the uncertainty of the ranking scores for an uncertainty-aware, post hoc approach to bias mitigation. We compare our proposed method with existing baselines for bias mitigation with respect to the utility-fairness trade-off, the controllability of methods, and computational costs. We show that an uncertainty-based approach can provide an intuitive and flexible trade-off that outperforms all baselines without additional training requirements, allowing for the post hoc use of this approach on top of arbitrary retrieval models

ALE Meta-Analysis Workflows Via the Brainmap Database: Progress Towards A Probabilistic Functional Brain Atlas

With the ever-increasing number of studies in human functional brain mapping, an abundance of data has been generated that is ready to be synthesized and modeled on a large scale. The BrainMap database archives peak coordinates from published neuroimaging studies, along with the corresponding metadata that summarize the experimental design. BrainMap was designed to facilitate quantitative meta-analysis of neuroimaging results reported in the literature and supports the use of the activation likelihood estimation (ALE) method. In this paper, we present a discussion of the potential analyses that are possible using the BrainMap database and coordinate-based ALE meta-analyses, along with some examples of how these tools can be applied to create a probabilistic atlas and ontological system of describing function–structure correspondences