AXR1 acts after lateral bud formation to inhibit lateral bud growth in Arabidopsis

The AXR1 gene of Arabidopsis is required for many auxin responses. The highly branched shoot phenotype of mature axr1 mutant plants has been taken as genetic evidence for a role of auxin in the control of shoot branching. We compared the development of lateral shoots in wild-type Columbia and axr1-12 plants. In the wild type, the pattern of lateral shoot development depends on the developmental stage of the plant. During prolonged vegetative growth, axillary shoots arise and develop in a basal-apical sequence. After floral transition, axillary shoots arise rapidly along the primary shoot axis and grow out to form lateral inflorescences in an apical-basal sequence. For both patterns, the axr1 mutation does not affect the timing of axillary meristem formation; however, subsequent lateral shoot development proceeds more rapidly in axr1 plants. The outgrowth of lateral inflorescences from excised cauline nodes of wild-type plants is inhibited by apical auxin. axr1-12 nodes are resistant to this inhibition. These results provide evidence for common control of axillary growth in both patterns, and suggest a role for auxin during the late stages of axillary shoot development following the formation of the axillary bud and several axillary leaf primordia

Analysing Magnetism Using Scanning SQUID Microscopy

Scanning superconducting quantum interference device microscopy (SSM) is a scanning probe technique that images local magnetic flux, which allows for mapping of magnetic fields with high field and spatial accuracy. Many studies involving SSM have been published in the last decades, using SSM to make qualitative statements about magnetism. However, quantitative analysis using SSM has received less attention. In this work, we discuss several aspects of interpreting SSM images and methods to improve quantitative analysis. First, we analyse the spatial resolution and how it depends on several factors. Second, we discuss the analysis of SSM scans and the information obtained from the SSM data. Using simulations, we show how signals evolve as a function of changing scan height, SQUID loop size, magnetization strength and orientation. We also investigated 2-dimensional autocorrelation analysis to extract information about the size, shape and symmetry of magnetic features. Finally, we provide an outlook on possible future applications and improvements.Comment: 16 pages, 10 figure

Patterns of differential introgression in a salamander hybrid zone: inferences from genetic data and ecological niche modelling

Hybrid zones have yielded considerable insight into many evolutionary processes, including speciation and the maintenance of species boundaries. Presented here are analyses from a hybrid zone that occurs among three salamanders – Plethodon jordani , Plethodon metcalfi and Plethodon teyahalee – from the southern Appalachian Mountains. Using a novel statistical approach for analysis of non-clinal, multispecies hybrid zones, we examined spatial patterns of variation at four markers: single-nucleotide polymorphisms (SNPs) located in the mtDNA ND2 gene and the nuclear DNA ILF3 gene, and the morphological markers of red cheek pigmentation and white flecks. Concordance of the ILF3 marker and both morphological markers across four transects is observed. In three of the four transects, however, the pattern of mtDNA is discordant from all other markers, with a higher representation of P. metcalfi mtDNA in the northern and lower elevation localities than is expected given the ILF3 marker and morphology. To explore whether climate plays a role in the position of the hybrid zone, we created ecological niche models for P. jordani and P. metcalfi . Modelling results suggest that hybrid zone position is not determined by steep gradients in climatic suitability for either species. Instead, the hybrid zone lies in a climatically homogenous region that is broadly suitable for both P. jordani and P. metcalfi . We discuss various selective (natural selection associated with climate) and behavioural processes (sex-biased dispersal, asymmetric reproductive isolation) that might explain the discordance in the extent to which mtDNA and nuclear DNA and colour-pattern traits have moved across this hybrid zone.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79135/1/j.1365-294X.2010.04796.x.pd

Modelling Ultrasonic Inspection of Rough Defects

Ultrasonic signals are affected by the nature of the defects under investigation. One defect property known to alter signal amplitudes and pulse shapes is surface roughness. No exact theory is available to describe the interaction of ultrasonic waves with rough defects but approximate theories are of great value, over various regimes of validity [1,2]. We have combined one such approximation. Kirchhoff theory [1,2], with many aspects of a real inspection system, to provide a model for simulating the ultrasonic inspection of randomly rough defects. The model is currently acoustic, such that mode conversion effects cannot be predicted. This paper presents some details of the model, together with sample results. These include a comparison with experimental measurements from rough surfaces, showing favourable agreement

UK sustainable drainage systems: past, present and future

Urban drainage has developed from an engineering discipline, concerned principally with public health and safety outcomes, into a multifaceted vision linking drainage with environmental and wider social and economic imperatives to deliver multifunctional outcomes. UK attention is too often focused on surface water as ‘a problem’, despite international progress and initiatives showing that an ‘opportunity-centred’ approach needs to be taken. Sustainable drainage systems, or ‘Suds’, can, when they are part of an integrated approach to water management, cost-effectively provide many benefits beyond management of water quality and quantity. New tools are available that can design Suds for maximum value to society but this requires greater collaboration across disciplines to seize all of the opportunities available. This paper introduces those tools and a roadmap for their use, including guidance, design objectives and criteria for maximising benefits. These new supporting tools and guidance can help to provide a business case for greater use of Suds in future

Linear Versus Nonlinear Methods for Detecting Magnetospheric and Ionospheric Current Systems Patterns

Abstract There is a growing interest in the development of models and methods of analysis aimed to recognize in the geomagnetic field signals the different contributions coming from the various sources both internal and external to the Earth. Many models describing the geomagnetic field of internal and external origin have been developed. Here, we investigate the possibility to recognize in the magnetic field of external origin the different contributions coming from external sources. We consider the measurements of the vertical component of the geomagnetic field recorded by the European Space Agency (ESA) Swarm A and B satellites at low and mid latitudes during a geomagnetically quiet period. We apply two different methods of analysis: a linear method, that is, the empirical orthogonal function (EOF), and a nonlinear one, that is, the multivariate empirical mode decomposition (MEMD). Due to the high nonlinear behavior of the different external contributions to the magnetic signal the MEMD seems to recognize better than EOF the main intrinsic modes capable of describing the different magnetic spatial structures embedded in the analyzed signal. By applying the MEMD only five modes and a residue are necessary to recognize the different contributions coming from the external sources in the magnetic signal against the 26 modes that are necessary in the case of the EOF. This study is an example of the potential of the MEMD to give new insights into the analysis of the geomagnetic field of external origin and to separate the ionospheric signal from the magnetospheric one in a simple and rapid way

Long-Term Stability of an Area-Reversible Atom-Interferometer Sagnac Gyroscope

We report on a study of the long-term stability and absolute accuracy of an atom interferometer gyroscope. This study included the implementation of an electro-optical technique to reverse the vector area of the interferometer for reduced systematics and a careful study of systematic phase shifts. Our data strongly suggests that drifts less than 96 $\mu$deg/hr are possible after empirically removing shifts due to measured changes in temperature, laser intensity, and several other experimental parameters.Comment: 4 pages, 4 figures, submitted to PR

Which solar EUV indices are best for reconstructing the solar EUV irradiance ?

The solar EUV irradiance is of key importance for space weather. Most of the time, however, surrogate quantities such as EUV indices have to be used by lack of continuous and spectrally resolved measurements of the irradiance. The ability of such proxies to reproduce the irradiance from different solar atmospheric layers is usually investigated by comparing patterns of temporal correlations. We consider instead a statistical approach. The TIMED/SEE experiment, which has been continuously operating since Feb. 2002, allows for the first time to compare in a statistical manner the EUV spectral irradiance to five EUV proxies: the sunspot number, the f10.7, Ca K, and Mg II indices, and the He I equivalent width. Using multivariate statistical methods such as multidimensional scaling, we represent in a single graph the measure of relatedness between these indices and various strong spectral lines. The ability of each index to reproduce the EUV irradiance is discussed; it is shown why so few lines can be effectively reconstructed from them. All indices exhibit comparable performance, apart from the sunspot number, which is the least appropriate. No single index can satisfactorily describe both the level of variability on time scales beyond 27 days, and relative changes of irradiance on shorter time scales.Comment: 6 figures, to appear in Adv. Space. Re

The Ubiquity of the rms-flux relation in Black Hole X-ray Binaries

We have investigated the short term linear relation between the rms variability and the flux in 1,961 observations of 9 black hole X-ray binaries. The rms-flux relation for the 1-10 Hz range is ubiquitously observed in any observation with good variability signal to noise (> 3 % 1-10 Hz fractional rms). This concurs with results from a previous study of Cygnus X-1 (Gleissner et. al. 2004), and extends detection of the rms-flux relation to a wider range of states. We find a strong dependence of the flux intercept of the rms-flux relation on source state; as the source transitions from the hard state into the hard intermediate state the intercept becomes strongly positive. We find little evidence for flux dependence of the broad-band noise within the PSD shape, excepting a small subset of observations from one object in an anomalous soft-state. We speculate that the ubiquitous linear rms-flux relation in the broad band noise of this sample, representing a range of different states and objects, indicates that its formation mechanism is an essential property of the luminous accretion flow around black holes.Comment: 12 pages, 6 figures, accepted for publication in MNRA

Data mining: a tool for detecting cyclical disturbances in supply networks.

Disturbances in supply chains may be either exogenous or endogenous. The ability automatically to detect, diagnose, and distinguish between the causes of disturbances is of prime importance to decision makers in order to avoid uncertainty. The spectral principal component analysis (SPCA) technique has been utilized to distinguish between real and rogue disturbances in a steel supply network. The data set used was collected from four different business units in the network and consists of 43 variables; each is described by 72 data points. The present paper will utilize the same data set to test an alternative approach to SPCA in detecting the disturbances. The new approach employs statistical data pre-processing, clustering, and classification learning techniques to analyse the supply network data. In particular, the incremental k-means clustering and the RULES-6 classification rule-learning algorithms, developed by the present authors’ team, have been applied to identify important patterns in the data set. Results show that the proposed approach has the capability automatically to detect and characterize network-wide cyclical disturbances and generate hypotheses about their root cause