Second-order QCD corrections to event shape distributions in deep inelastic scattering

We compute the next-to-next-to-leading order (NNLO) QCD corrections to event shape distributions and their mean values in deep inelastic lepton–nucleon scattering. The magnitude and shape of the corrections varies considerably between different variables. The corrections reduce the renormalization and factorization scale uncertainty of the predictions. Using a dispersive model to describe non-perturbative power corrections, we compare the NNLO QCD predictions with data from the H1 and ZEUS experiments. The newly derived corrections improve the theory description of the distributions and of their mean values

Yeah, Right, Uh-Huh: A Deep Learning Backchannel Predictor

Using supporting backchannel (BC) cues can make human-computer interaction more social. BCs provide a feedback from the listener to the speaker indicating to the speaker that he is still listened to. BCs can be expressed in different ways, depending on the modality of the interaction, for example as gestures or acoustic cues. In this work, we only considered acoustic cues. We are proposing an approach towards detecting BC opportunities based on acoustic input features like power and pitch. While other works in the field rely on the use of a hand-written rule set or specialized features, we made use of artificial neural networks. They are capable of deriving higher order features from input features themselves. In our setup, we first used a fully connected feed-forward network to establish an updated baseline in comparison to our previously proposed setup. We also extended this setup by the use of Long Short-Term Memory (LSTM) networks which have shown to outperform feed-forward based setups on various tasks. Our best system achieved an F1-Score of 0.37 using power and pitch features. Adding linguistic information using word2vec, the score increased to 0.39

NNLO QCD corrections to event orientation in e+e- annihilation

We present a new implementation of the NNLO QCD corrections to three-jet final states and related event-shape observables in electron–positron annihilation. Our implementation is based on the antenna subtraction method, and is performed in the NNLOjet framework. The calculation improves upon earlier results by taking into account the full kinematical information on the initial state momenta, thereby allowing the event orientation to be computed to NNLO accuracy. We find the event-orientation distributions at LEP and SLC to be very robust under higher order QCD corrections

High throughput data streaming of individual longitudinal electron bunch profiles in a storage ring with single-shot electro-optical sampling

The development of fast detection methods for comprehensive monitoring of electron bunches is a prerequisite to gain comprehensive control over the synchrontron emission in storage rings with their MHz repetition rate. Here, we present a proof-of-principle experiment with at detailed description of our implementation to detect the longitudinal electron bunch profiles via single-shot, near-field electro-optical sampling at the Karlsruhe Research Accelerator (KARA). Our experiment is equipped with an ultra-fast line array camera providing a high-throughput MHz data stream. We characterize statistical properties of the obtained data set and give a detailed description for the data processing as well as for the calculation of the charge density profiles, which where measured in the short-bunch operation mode of KARA. Finally, we discuss properties of the bunch profile dynamics on a coarse-grained level on the example of the well-known synchrotron oscillation.Comment: 8 pages, 5 figure

Induction maintenance concept for HAART as initial treatment in HIV infected infants

<p>Abstract</p> <p>Background</p> <p>Early initiated antiretroviral therapy (ART) in HIV infected infants leads to improved long-term viral suppression and survival. Guidelines recommend initiating therapy with a triple ART consisting of two nucleoside reverse transcriptase inhibitors (NRTIs) and either one additional non-nucleoside reverse transcriptase inhibitor (NNRTI) or a protease inhibitor (PI). Compared to older children and adults, viral relapse is seen more frequently in infants receiving triple ART. We now address the possibility of a more potent ART with a quadruple induction and triple maintenance therapy.</p> <p>Methods</p> <p>We examine the longitudinal course in four HIV infected infants, who were referred from other centers and could not be recruited to multicentre trials. We introduced ART initially consisting of two NRTIs, one NNRTI and one PI and later discontinued the PI at the age of 12 months maintaining a triple regime consisting of two NRTIs and one NNRTI.</p> <p>Results</p> <p>Provided that therapy adherence was maintained we observed an effective sustained decline of viral load and significant CD4 cell reconstitution even after switching to a triple regime. No drug associated toxicity was seen.</p> <p>Conclusion</p> <p>We suggest that a four drug therapy might be a possible initial therapy option in HIV infected infants, at least in those with a high viral load, followed by a maintenance triple regime after 12 months of therapy.</p

Overview of the IWSLT 2017 Evaluation Campaign

The IWSLT 2017 evaluation campaign has organised three tasks. The Multilingual task, which is about training machine translation systems handling many-to-many language directions, including so-called zero-shot directions. The Dialogue task, which calls for the integration of context information in machine translation, in order to resolve anaphoric references that typically occur in human-human dialogue turns. And, finally, the Lecture task, which offers the challenge of automatically transcribing and translating real-life university lectures. Following the tradition of these reports, we will described all tasks in detail and present the results of all runs submitted by their participants

Simultaneous Detection of Longitudinal and Transverse Bunch Signals at a Storage Ring

To understand and control the dynamics in the longitudinal phase space, time-resolved measurements of different bunch parameters are required. For a reconstruction of this phase space, the detector systems have to be synchronized. This reconstruction can be used e.g. for studies of the micro-bunching instability. It occurs if the interaction of the bunch with its own radiation leads to the formation of sub-structures on the longitudinal bunch profile. These sub-structures can grow rapidly -- leading to a sawtooth-like behaviour of the bunch. At KARA, we use a fast-gated intensified camera for energy spread studies, Schottky diodes for coherent synchrotron radiation studies as well as electro-optical spectral decoding for longitudinal bunch profile measurements. For a synchronization, a hardware synchronization scheme is used which compensates for eventual hardware delays. In this paper, the different experimental setups and their synchronization are discussed and first results of synchronous measurements are presented

Benchmarking Deep Learning Models for Tooth Structure Segmentation.

A wide range of deep learning (DL) architectures with varying depths are available, with developers usually choosing one or a few of them for their specific task in a nonsystematic way. Benchmarking (i.e., the systematic comparison of state-of-the art architectures on a specific task) may provide guidance in the model development process and may allow developers to make better decisions. However, comprehensive benchmarking has not been performed in dentistry yet. We aimed to benchmark a range of architecture designs for 1 specific, exemplary case: tooth structure segmentation on dental bitewing radiographs. We built 72 models for tooth structure (enamel, dentin, pulp, fillings, crowns) segmentation by combining 6 different DL network architectures (U-Net, U-Net++, Feature Pyramid Networks, LinkNet, Pyramid Scene Parsing Network, Mask Attention Network) with 12 encoders from 3 different encoder families (ResNet, VGG, DenseNet) of varying depth (e.g., VGG13, VGG16, VGG19). On each model design, 3 initialization strategies (ImageNet, CheXpert, random initialization) were applied, resulting overall into 216 trained models, which were trained up to 200 epochs with the Adam optimizer (learning rate = 0.0001) and a batch size of 32. Our data set consisted of 1,625 human-annotated dental bitewing radiographs. We used a 5-fold cross-validation scheme and quantified model performances primarily by the F1-score. Initialization with ImageNet or CheXpert weights significantly outperformed random initialization (P < 0.05). Deeper and more complex models did not necessarily perform better than less complex alternatives. VGG-based models were more robust across model configurations, while more complex models (e.g., from the ResNet family) achieved peak performances. In conclusion, initializing models with pretrained weights may be recommended when training models for dental radiographic analysis. Less complex model architectures may be competitive alternatives if computational resources and training time are restricting factors. Models developed and found superior on nondental data sets may not show this behavior for dental domain-specific tasks

Calculations for deep inelastic scattering using fast interpolation grid techniques at NNLO in QCD and the extraction of αs from HERA data

The extension of interpolation-grid frameworks for perturbative QCD calculations at next-to-next-to-leading order (NNLO) is presented for deep inelastic scattering (DIS) processes. A fast and flexible evaluation of higher-order predictions for any a posteriori choice of parton distribution functions (PDFs) or value of the strong coupling constant is essential in iterative fitting procedures to extract PDFs and Standard Model parameters as well as for a detailed study of the scale dependence. The APPLfast project, described here, provides a generic interface between the parton-level Monte Carlo program NNLOjet and both the APPLgrid and fastNLO libraries for the production of interpolation grids at NNLO accuracy. Details of the interface for DIS processes are presented together with the required interpolation grids at NNLO, which are made available. They cover numerous inclusive jet measurements by the H1 and ZEUS experiments at HERA. An extraction of the strong coupling constant is performed as an application of the use of such grids and a best-fit value of αs(MZ)=0.1170(15)exp(25)th is obtained using the HERA inclusive jet cross section data