Estimating Spectroscopic Redshifts by Using k Nearest Neighbors Regression I. Description of Method and Analysis

Context: In astronomy, new approaches to process and analyze the exponentially increasing amount of data are inevitable. While classical approaches (e.g. template fitting) are fine for objects of well-known classes, alternative techniques have to be developed to determine those that do not fit. Therefore a classification scheme should be based on individual properties instead of fitting to a global model and therefore loose valuable information. An important issue when dealing with large data sets is the outlier detection which at the moment is often treated problem-orientated. Aims: In this paper we present a method to statistically estimate the redshift z based on a similarity approach. This allows us to determine redshifts in spectra in emission as well as in absorption without using any predefined model. Additionally we show how an estimate of the redshift based on single features is possible. As a consequence we are e.g. able to filter objects which show multiple redshift components. We propose to apply this general method to all similar problems in order to identify objects where traditional approaches fail. Methods: The redshift estimation is performed by comparing predefined regions in the spectra and applying a k nearest neighbor regression model for every predefined emission and absorption region, individually. Results: We estimated a redshift for more than 50% of the analyzed 16,000 spectra of our reference and test sample. The redshift estimate yields a precision for every individually tested feature that is comparable with the overall precision of the redshifts of SDSS. In 14 spectra we find a significant shift between emission and absorption or emission and emission lines. The results show already the immense power of this simple machine learning approach for investigating huge databases such as the SDSS.Comment: accepted for publication in A&

Bose-Einstein condensation in a circular waveguide

We have produced Bose-Einstein condensates in a ring-shaped magnetic waveguide. The few-millimeter diameter non-zero bias ring is formed from a time-averaged quadrupole ring. Condensates which propagate around the ring make several revolutions within the time it takes for them to expand to fill the ring. The ring shape is ideally suited for studies of vorticity in a multiply-connected geometry and is promising as a rotation sensor.Comment: 4 pages, 4 figure

Optimized pharmacological control over the AAV-Gene-Switch vector for regulable gene therapy.

Gene therapy in its current design is an irreversible process. It cannot be stopped in case of unwanted side effects, nor can expression levels of therapeutics be adjusted to individual patient's needs. Thus, the Gene-Switch (GS) system for pharmacologically regulable neurotrophic factor expression was established for treatment of parkinsonian patients. Mifepristone, the synthetic steroid used to control transgene expression of the GS vector, is an approved clinical drug. However, pharmacokinetics and -dynamics of mifepristone vary considerably between different experimental animal species and depend on age and gender. In humans, but not in any other species, mifepristone binds to a high-affinity plasma carrier protein. We now demonstrate that the formulation of mifepristone can have robust impact on its ability to activate the GS system. Furthermore, we show that a pharmacological booster, ritonavir (Rtv), robustly enhances the pharmacological effect of mifepristone, and allows it to overcome gender- and species-specific pharmacokinetic and -dynamic issues. Most importantly, we demonstrate that the GS vector can be efficiently controlled by mifepristone in the presence of its human plasma carrier protein, α1-acid glycoprotein, in a "humanized" rat model. Thus, we have substantially improved the applicability of the GS vector toward therapeutic use in patients

Bound States and Threshold Resonances in Quantum Wires with Circular Bends

We study the solutions to the wave equation in a two-dimensional tube of unit width comprised of two straight regions connected by a region of constant curvature. We introduce a numerical method which permits high accuracy at high curvature. We determine the bound state energies as well as the transmission and reflection matrices, ${\cal T}$ and ${\cal R}$ and focus on the nature of the resonances which occur in the vicinity of channel thresholds. We explore the dependence of these solutions on the curvature of the tube and angle of the bend and discuss several limiting cases where our numerical results confirm analytic predictions.Comment: 24 pages, revtex file, one style file and 17 PostScript figures include

FastSurfer-HypVINN: Automated sub-segmentation of the hypothalamus and adjacent structures on high-resolutional brain MRI

The hypothalamus plays a crucial role in the regulation of a broad range of physiological, behavioural, and cognitive functions. However, despite its importance, only a few small-scale neuroimaging studies have investigated its substructures, likely due to the lack of fully automated segmentation tools to address scalability and reproducibility issues of manual segmentation. While the only previous attempt to automatically sub-segment the hypothalamus with a neural network showed promise for 1.0 mm isotropic T1-weighted (T1w) MRI, there is a need for an automated tool to sub-segment also high-resolutional (HiRes) MR scans, as they are becoming widely available, and include structural detail also from multi-modal MRI. We, therefore, introduce a novel, fast, and fully automated deep learning method named HypVINN for sub-segmentation of the hypothalamus and adjacent structures on 0.8 mm isotropic T1w and T2w brain MR images that is robust to missing modalities. We extensively validate our model with respect to segmentation accuracy, generalizability, in-session test-retest reliability, and sensitivity to replicate hypothalamic volume effects (e.g. sex-differences). The proposed method exhibits high segmentation performance both for standalone T1w images as well as for T1w/T2w image pairs. Even with the additional capability to accept flexible inputs, our model matches or exceeds the performance of state-of-the-art methods with fixed inputs. We, further, demonstrate the generalizability of our method in experiments with 1.0 mm MR scans from both the Rhineland Study and the UK Biobank. Finally, HypVINN can perform the segmentation in less than a minute (GPU) and will be available in the open source FastSurfer neuroimaging software suite, offering a validated, efficient, and scalable solution for evaluating imaging-derived phenotypes of the hypothalamus.Comment: Submitted to Imaging Neuroscienc

Surfactants tailored by the class Actinobacteria

Globally the change towards the establishment of a bio-based economy has resulted in an increased need for bio-based applications. This, in turn, has served as a driving force for the discovery and application of novel biosurfactants. The class Actinobacteria represents a vast group of microorganisms with the ability to produce a diverse range of secondary metabolites, including surfactants. Understanding the extensive nature of the biosurfactants produced by actinobacterial strains can assist in finding novel biosurfactants with new potential applications. This review therefore presents a comprehensive overview of the knowledge available on actinobacterial surfactants, the chemical structures that have been completely or partly elucidated, as well as the identity of the biosurfactant-producing strains. Producer strains of not yet elucidated compounds are discussed, as well as the original habitats of all the producer strains, which seems to indicate that biosurfactant production is environmentally driven. Methodology applied in the isolation, purification and structural elucidation of the different types of surface active compounds, as well as surfactant activity tests, are also discussed. Overall, actinobacterial surfactants can be summarized to include the dominantly occurring trehalose-comprising surfactants, other non-trehalose containing glycolipids, lipopeptides and the more rare actinobacterial surfactants. The lack of structural information on a large proportion of actinobacterial surfactants should be considered as a driving force to further explore the abundance and diversity of these compounds. This would allow for a better understanding of actinobacterial surface active compounds and their potential for biotechnological application

Surfactants tailored by the class Actinobacteria

Globally the change towards the establishment of a bio-based economy has resulted in an increased need for bio-based applications. This, in turn, has served as a driving force for the discovery and application of novel biosurfactants. The class Actinobacteria represents a vast group of microorganisms with the ability to produce a diverse range of secondary metabolites, including surfactants. Understanding the extensive nature of the biosurfactants produced by actinobacterial strains can assist in finding novel biosurfactants with new potential applications. This review therefore presents a comprehensive overview of the knowledge available on actinobacterial surfactants, the chemical structures that have been completely or partly elucidated, as well as the identity of the biosurfactant-producing strains. Producer strains of not yet elucidated compounds are discussed, as well as the original habitats of all the producer strains, which seems to indicate that biosurfactant production is environmentally driven. Methodology applied in the isolation, purification and structural elucidation of the different types of surface active compounds, as well as surfactant activity tests, are also discussed. Overall, actinobacterial surfactants can be summarized to include the dominantly occurring trehalose-comprising surfactants, other non-trehalose containing glycolipids, lipopeptides and the more rare actinobacterial surfactants. The lack of structural information on a large proportion of actinobacterial surfactants should be considered as a driving force to further explore the abundance and diversity of these compounds. This would allow for a better understanding of actinobacterial surface active compounds and their potential for biotechnological application

Notions and subnotions in information structure

Three dimensions can be distinguished in a cross-linguistic account of information structure. First, there is the definition of the focus constituent, the part of the linguistic expression which is subject to some focus meaning. Second and third, there are the focus meanings and the array of structural devices that encode them. In a given language, the expression of focus is facilitated as well as constrained by the grammar within which the focus devices operate. The prevalence of focus ambiguity, the structural inability to make focus distinctions, will thus vary across languages, and within a language, across focus meanings

CD20 and CD19 targeted vectors induce minimal activation of resting B lymphocytes

B lymphocytes are an important cell population of the immune system. However, until recently it was not possible to transduce resting B lymphocytes with retro- or lentiviral vectors, making them unsusceptible for genetic manipulations by these vectors. Lately, we demonstrated that lentiviral vectors pseudotyped with modified measles virus (MV) glycoproteins hemagglutinin, responsible for receptor recognition, and fusion protein were able to overcome this transduction block. They use either the natural MV receptors, CD46 and signaling lymphocyte activation molecule (SLAM), for cell entry (MV-LV) or the vector particles were further modified to selectively enter via the CD20 molecule, which is exclusively expressed on B lymphocytes (CD20-LV). It has been shown previously that transduction by MV-LV does not induce B lymphocyte activation. However, if this is also true for CD20-LV is still unknown. Here, we generated a vector specific for another B lymphocyte marker, CD19, and compared its ability to transduce resting B lymphocytes with CD20-LV. The vector (CD19ds-LV) was able to stably transduce unstimulated B lymphocytes, albeit with a reduced efficiency of about 10% compared to CD20-LV, which transduced about 30% of the cells. Since CD20 as well as CD19 are closely linked to the B lymphocyte activation pathway, we investigated if engagement of CD20 or CD19 molecules by the vector particles induces activating stimuli in resting B lymphocytes. Although, activation of B lymphocytes often involves calcium influx, we did not detect elevated calcium levels. However, the activation marker CD71 was substantially up-regulated upon CD20-LV transduction and most importantly, B lymphocytes transduced with CD20-LV or CD19ds-LV entered the G1b phase of cell cycle, whereas untransduced or MV-LV transduced B lymphocytes remained in G0. Hence, CD20 and CD19 targeting vectors induce activating stimuli in resting B lymphocytes, which most likely renders them susceptible for lentiviral vector transduction

Magnetic trapping of ultracold neutrons

Three-dimensional magnetic confinement of neutrons is reported. Neutrons are loaded into an Ioffe-type superconducting magnetic trap through inelastic scattering of cold neutrons with 4He. Scattered neutrons with sufficiently low energy and in the appropriate spin state are confined by the magnetic field until they decay. The electron resulting from neutron decay produces scintillations in the liquid helium bath that results in a pulse of extreme ultraviolet light. This light is frequency downconverted to the visible and detected. Results are presented in which 500 +/- 155 neutrons are magnetically trapped in each loading cycle, consistent with theoretical predictions. The lifetime of the observed signal, 660 s +290/-170 s, is consistent with the neutron beta-decay lifetime.Comment: 17 pages, 18 figures, accepted for publication in Physical Review