Technical University of Berlin

About: Technical University of Berlin is a education organization based out in Berlin, Germany. It is known for research contribution in the topics: Laser & Catalysis. The organization has 27292 authors who have published 59342 publications receiving 1414623 citations. The organization is also known as: Technische Universität Berlin & TU Berlin.

Electronic Structure Makes a Difference: Cytochrome P-450 Mediated Hydroxylations of Hydrocarbons as a Two-State Reactivity Paradigm

Abstract: This paper describes a reactivity paradigm called two-state reactivity (TSR) in C ± H bond activation by metal oxenoid cations (e.g., FeO‡). The paradigm is applied to the hydroxylation of alkanes by the active species of the enzyme cytochrome P-450, and a mechanistic scheme is proposed based on the competition between TSR pathways and single-state-reactivity (SSR) pathways. Generally, the oxide cations of the late transition metals (MO‡) possess the same bonding patterns as the O2 molecule, having a high-spin ground state and an adjacent low-spin excited state. The adjacency of the spin states, together with the poor bonding capability of the high-spin state and the good bonding capability of the low-spin state, leads to a spin crossover along the reaction coordinate and opens a low-energy TSR path for hydroxylation. The competing pathway is SSR, in which the reaction starts, occurs and ends in the same spin state. The TSR/SSR competition is modulated by the probability of spin crossover. Generally, TSR involves concerted pathways that conserve stereochemical information, while SSR results in stepwise mechanisms that scramble this information. The TSR/SSR competition is used to shed some light on recent results which are at odds with the commonly accepted mechanism of P-450 hydroxylation. The fundamental features of the paradigm are outlined and the theoretical and experimental challenges for its articulation are spelled out.

A Unifying Review of Deep and Shallow Anomaly Detection

Abstract: Deep learning approaches to anomaly detection have recently improved the state of the art in detection performance on complex datasets such as large collections of images or text. These results have sparked a renewed interest in the anomaly detection problem and led to the introduction of a great variety of new methods. With the emergence of numerous such methods, including approaches based on generative models, one-class classification, and reconstruction, there is a growing need to bring methods of this field into a systematic and unified perspective. In this review we aim to identify the common underlying principles as well as the assumptions that are often made implicitly by various methods. In particular, we draw connections between classic 'shallow' and novel deep approaches and show how this relation might cross-fertilize or extend both directions. We further provide an empirical assessment of major existing methods that is enriched by the use of recent explainability techniques, and present specific worked-through examples together with practical advice. Finally, we outline critical open challenges and identify specific paths for future research in anomaly detection.

Looking glass: a field study on noticing interactivity of a shop window

Abstract: In this paper we present our findings from a lab and a field study investigating how passers-by notice the interactivity of public displays. We designed an interactive installation that uses visual feedback to the incidental movements of passers-by to communicate its interactivity. The lab study reveals: (1) Mirrored user silhouettes and images are more effective than avatar-like representations. (2) It takes time to notice the interactivity (approx. 1.2s). In the field study, three displays were installed during three weeks in shop windows, and data about 502 interaction sessions were collected. Our observations show: (1) Significantly more passers-by interact when immediately showing the mirrored user image (+90%) or silhouette (+47%) compared to a traditional attract sequence with call-to-action. (2) Passers-by often notice interactivity late and have to walk back to interact (the landing effect). (3) If somebody is already interacting, others begin interaction behind the ones already interacting, forming multiple rows (the honeypot effect). Our findings can be used to design public display applications and shop windows that more effectively communicate interactivity to passers-by.