A Transactional Analysis of Interaction Free Measurements

The transactional interpretation of quantum mechanics is applied to the "interaction-free" measurement scenario of Elitzur and Vaidman and to the Quantum Zeno Effect version of the measurement scenario by Kwiat, et al. It is shown that the non-classical information provided by the measurement scheme is supplied by the probing of the intervening object by incomplete offer and confirmation waves that do not form complete transactions or lead to real interactions.Comment: Accepted for publication in Foundations of Physics Letter

Untersuchungen zur Motilität von Sorbitol-fermentierenden enterohämorrhagischen Escherichia coli O157

Sorbitol-fermentierende enterohämorrhagische Escherichia coli (EHEC) O157:H- gelten als unbeweglich und exprimieren kein H-Antigen. An 10 Stämmen SF EHEC O157 wurde untersucht, ob sich Motilität durch Passage in semisolidem Agar induzieren lässt. fliC sowie ein Gen des Master-Operons flhC wurden im Hinblick auf vorbeschriebene Mutationen untersucht, die mit dem Verlust an Motilität in EHEC O157:H- in Verbindung gebracht werden. Motile Stämme wurden auf die Expression von H7-Antigen sowie auf das Vorhandensein von Flagellen untersucht. Alle untersuchten EHEC O157:H- verfügten über eine typische Kombination bestimmter für Virulenzfaktoren kodierender Gene. Sie beherbergten ein intaktes fliC. In flhC ließ sich in allen Stämmen eine in der Literatur vorbeschriebene Deletion nachweisen. Motilität ließ sich in allen Stämmen beobachten. Drei zeigten die Expression von H7-Antigen. Elektronenmikroskopisch zeigten sich fimbrienartige Organellen, die an unbeweglichen Organismen nicht zur Darstellung kamen. Es konnte gezeigt werden, dass die vorbeschriebene Deletion in flhC die Entwicklung von Motilität in EHEC O157:H- nicht verhindert

Structural basis of TFIIH activation for nucleotide excision repair.

Nucleotide excision repair (NER) is the major DNA repair pathway that removes UV-induced and bulky DNA lesions. There is currently no structure of NER intermediates, which form around the large multisubunit transcription factor IIH (TFIIH). Here we report the cryo-EM structure of an NER intermediate containing TFIIH and the NER factor XPA. Compared to its transcription conformation, the TFIIH structure is rearranged such that its ATPase subunits XPB and XPD bind double- and single-stranded DNA, consistent with their translocase and helicase activities, respectively. XPA releases the inhibitory kinase module of TFIIH, displaces a 'plug' element from the DNA-binding pore in XPD, and together with the NER factor XPG stimulates XPD activity. Our results explain how TFIIH is switched from a transcription to a repair factor, and provide the basis for a mechanistic analysis of the NER pathway

Diagnostic criteria for grading the severity of acute motion sickness

Diagnostic criteria for grading severity of acute motion sicknes

Describing and Understanding Neighborhood Characteristics through Online Social Media

Geotagged data can be used to describe regions in the world and discover local themes. However, not all data produced within a region is necessarily specifically descriptive of that area. To surface the content that is characteristic for a region, we present the geographical hierarchy model (GHM), a probabilistic model based on the assumption that data observed in a region is a random mixture of content that pertains to different levels of a hierarchy. We apply the GHM to a dataset of 8 million Flickr photos in order to discriminate between content (i.e., tags) that specifically characterizes a region (e.g., neighborhood) and content that characterizes surrounding areas or more general themes. Knowledge of the discriminative and non-discriminative terms used throughout the hierarchy enables us to quantify the uniqueness of a given region and to compare similar but distant regions. Our evaluation demonstrates that our model improves upon traditional Naive Bayes classification by 47% and hierarchical TF-IDF by 27%. We further highlight the differences and commonalities with human reasoning about what is locally characteristic for a neighborhood, distilled from ten interviews and a survey that covered themes such as time, events, and prior regional knowledgeComment: Accepted in WWW 2015, 2015, Florence, Ital

Influence of thickness and interface on the low-temperature enhancement of the spin Seebeck effect in YIG films

The temperature dependent longitudinal spin Seebeck effect (LSSE) in heavy metal (HM)/Y3Fe5O12 (YIG) hybrid structures is investigated as a function of YIG film thickness, magnetic field strength, and different HM detection material. The LSSE signal shows a large enhancement with reducing the temperature, leading to a pronounced peak at low temperatures. We find the LSSE peak temperature strongly depends on the film thickness as well as on the magnetic field. Our result can be well explained in the framework of magnon-driven LSSE by taking into account the temperature dependent effective propagation length of thermally excited magnons in bulk. We further demonstrate that the LSSE peak is significantly shifted by changing the interface coupling to an adjacent detection layer, revealing a more complex behavior beyond the currently discussed bulk effect. By direct microscopic imaging of the interface, we correlate the observed temperature dependence with the interface structure between the YIG and the adjacent metal layer. Our results highlight the role of interface effects on the temperature dependent LSSE in HM/YIG system, suggesting that the temperature dependent spin current transparency strikingly relies on the interface conditions

Predicting Rainfall in the Context of Rainfall Derivatives Using Genetic Programming

Rainfall is one of the most challenging variables to predict, as it exhibits very unique characteristics that do not exist in other time series data. Moreover, rainfall is a major component and is essential for applications that surround water resource planning. In particular, this paper is interested in the prediction of rainfall for rainfall derivatives. Currently in the rainfall derivatives literature, the process of predicting rainfall is dominated by statistical models, namely using a Markov-chain extended with rainfall prediction (MCRP). In this paper we outline a new methodology to be carried out by predicting rainfall with Genetic Programming (GP). This is the first time in the literature that GP is used within the context of rainfall derivatives. We have created a new tailored GP to this problem domain and we compare the performance of the GP and MCRP on 21 different data sets of cities across Europe and report the results. The goal is to see whether GP can outperform MCRP, which acts as a benchmark. Results indicate that in general GP significantly outperforms MCRP, which is the dominant approach in the literature