Dynamic Devensian ice flow in NE England: a sedimentological reconstruction

This study reconstructs the depositional environments that accompanied both ice advance and ice retreat of the last British–Irish Ice Sheet in NE England during the Last Glacial Maximum, and proposes three regional ice-flow phases. The Late Devensian (29–22 cal. ka BP) Tyne Gap Ice Stream initially deposited the Blackhall Till Formation during shelf-edge glaciation (Phase I). This subglacial traction till comprises several related facies, including stratified and laminated diamictons, tectonites, and sand and gravel beds deposited both in subglacial canals and in proglacial streams. Eventually, stagnation of the Tyne Gap Ice Stream led to ice-marginal sedimentation in County Durham (Phase II). During the Dimlington Stadial (21 cal. ka BP), the North Sea Lobe advanced towards the coastline of N Norfolk. This resulted initially in sandur deposition (widespread, tabular sand and gravel; the Peterlee Sand and Gravel Formation; Phase II) and ultimately in deposition of the Horden Till Formation (Phase III), a massive subglacial till. As the North Sea Lobe overrode previous formations, it thrusted and stacked sediments in County Durham, and dammed proglacial lakes between the east-coast ice, the Pennine uplands and the remaining Pennine ice. The North Sea Lobe retreated after Heinrich Event 1 (16 ka). This study highlights the complexity of ice flow during the Late Devensian glaciation of NE England, with changing environmental and oceanic conditions forcing a mobile and sensitive ice sheet.

Reconstruction of geomagnetic activity and near-Earth interplanetary conditions over the past 167 yr - Part 4: Near-Earth solar wind speed, IMF, and open solar flux

In the concluding paper of this tetralogy, we here use the different geomagnetic activity indices to reconstruct the near-Earth interplanetary magnetic field (IMF) and solar wind flow speed, as well as the open solar flux (OSF) from 1845 to the present day. The differences in how the various indices vary with near-Earth interplanetary parameters, which are here exploited to separate the effects of the IMF and solar wind speed, are shown to be statistically significant at the 93% level or above. Reconstructions are made using four combinations of different indices, compiled using different data and different algorithms, and the results are almost identical for all parameters. The correction to the aa index required is discussed by comparison with the Ap index from a more extensive network of mid-latitude stations. Data from the Helsinki magnetometer station is used to extend the aa index back to 1845 and the results confirmed by comparison with the nearby St Petersburg observatory. The optimum variations, using all available long-term geomagnetic indices, of the near-Earth IMF and solar wind speed, and of the open solar flux, are presented; all with ±2sigma� uncertainties computed using the Monte Carlo technique outlined in the earlier papers. The open solar flux variation derived is shown to be very similar indeed to that obtained using the method of Lockwood et al. (1999).

Reconstruction of geomagnetic activity and near-Earth interplanetary conditions over the past 167 yr - Part 3: improved representation of solar cycle 11

Svalgaard (2014) has recently pointed out that the calibration of the Helsinki magnetic observatory’s H component variometer was probably in error in published data for the years 1866–1874.5 and that this makes the interdiurnal variation index based on daily means, IDV(1d), (Lockwood et al., 2013a), and the interplanetary magnetic field strength derived from it (Lockwood et al., 2013b), too low around the peak of solar cycle 11. We use data from the modern Nurmijarvi station, relatively close to the site of the original Helsinki Observatory, to confirm a 30% underestimation in this interval and hence our results are fully consistent with the correction derived by Svalgaard. We show that the best method for recalibration uses the Helsinki Ak(H) and aa indices and is accurate to ±10 %. This makes it preferable to recalibration using either the sunspot number or the diurnal range of geomagnetic activity which we find to be accurate to ±20 %. In the case of Helsinki data during cycle 11, the two recalibration methods produce very similar corrections which are here confirmed using newly digitised data from the nearby St Petersburg observatory and also using declination data from Helsinki. However, we show that the IDV index is, compared to later years, too similar to sunspot number before 1872, revealing independence of the two data series has been lost; either because the geomagnetic data used to compile IDV has been corrected using sunspot numbers, or vice versa, or both. We present corrected data sequences for both the IDV(1d) index and the reconstructed IMF (interplanetary magnetic field).We also analyse the relationship between the derived near-Earth IMF and the sunspot number and point out the relevance of the prior history of solar activity, in addition to the contemporaneous value, to estimating any “floor” value of the near-Earth interplanetary field.

Centennial changes in solar activity and the response of galactic cosmic rays

There is a growing consensus that the eleven year modulation of galactic cosmic rays (GCRs) resulting from solar activity is related to interplanetary propagating diffusive barriers (PDBs). The source of these PDBs is not well understood and numerical models describing GCR modulation simulate their effect by scaling the diffusion tensor to the interplanetary magnetic field strength (IMF). The implications of a century-scale change in solar wind speed and open solar flux, for numerical modelling of GCR modulation and the reconstruction of GCR variations over the last hundred years are discussed. The dominant role of the solar non-axisymmetric magnetic field in both forcing longitudinal solar wind speed fluctuations at solar maximum and in increasing the IMF is discussed in the context of a long-term rise in the open solar magnetic flux.

Role of the Skyrme tensor force in heavy-ion fusion

We make use of the Skyrme effective nuclear interaction within the time-dependent Hartree-Fock framework to assess the effect of inclusion of the tensor terms of the Skyrme interaction on the fusion window of the 16O–16O reaction. We find that the lower fusion threshold, around the barrier, is quite insensitive to these details of the force, but the higher threshold, above which the nuclei pass through each other, changes by several MeV between different tensor parametrisations. The results suggest that eventually fusion properties may become part of the evaluation or fitting process for effective nuclear interactions.

Unrestricted Skyrme-tensor time-dependent Hartree-Fock model and its application to the nuclear response from spherical to triaxial nuclei

The nuclear time-dependent Hartree-Fock model formulated in three-dimensional space, based on the full standard Skyrme energy density functional complemented with the tensor force, is presented. Full self-consistency is achieved by the model. The application to the isovector giant dipole resonance is discussed in the linear limit, ranging from spherical nuclei (16O and 120Sn) to systems displaying axial or triaxial deformation (24Mg, 28Si, 178Os, 190W and 238U). Particular attention is paid to the spin-dependent terms from the central sector of the functional, recently included together with the tensor. They turn out to be capable of producing a qualitative change on the strength distribution in this channel. The effect on the deformation properties is also discussed. The quantitative effects on the linear response are small and, overall, the giant dipole energy remains unaffected. Calculations are compared to predictions from the (quasi)-particle random-phase approximation and experimental data where available, finding good agreement

The tensor-kinetic field in nuclear collisions

The role of the tensor terms in the Skyrme interaction is studied for their effect in dynamic calculations where non-zero contributions to the mean-field may arise, even when the starting nucleus, or nuclei are even-even and have no active time-odd potentials in the ground state. We study collisions in the test-bed 16O-16O system, and give a qualitative analysis of the behaviour of the time-odd tensor-kinetic density, which only appears in the mean field Hamiltonian in the presence of the tensor force. We find an axial excitation of this density is induced by a collision.

The effect of the tensor force on the predicted stability of superheavy nuclei

The effect of the tensor component of the Skyrme effective nucleon-nucleon interaction on the single-particle structure in superheavy elements is studied. A selection of the available Skyrme forces has been chosen and their predictions for the proton and neutron shell closures investigated. The inclusion of the tensor term with realistic coupling strength parameters leads to a small increase in the spin-orbit splitting between the proton 2f7/2 and 2f5/2 partners, opening the Z=114 shell gap over a wide range of nuclei. The Z=126 shell gap, predicted by these models in the absence of the tensor term, is found to be stongly dependent on neutron number with a Z=138 gap opening for large neutron numbers, having a consequent implication for the synthesis of neutron-rich superheavy elements. The predicted neutron shell structures remain largely unchanged by inclusion of the tensor component.

Revolution blues: the reconstruction of Health and Safety as a ‘common-sense’ form of regulation

This paper provides a review of the last five years of policymaking in the area of health and safety law; this includes multiple reviews, legislative reform, and the reframing of rhetoric around the issue. It characterises this as a process of social construction of a new ‘universe of meaning’ around health and safety regulation, which provides a basis for a particular, narrow, neoliberal conception of regulation and responsibility to permeate the mainstream. Deliberative and public-facing policymaking processes have been utilised as a key element of this process.

Dimensionality reduction assisted tensor clustering

This paper is concerned with tensor clustering with the assistance of dimensionality reduction approaches. A class of formulation for tensor clustering is introduced based on tensor Tucker decomposition models. In this formulation, an extra tensor mode is formed by a collection of tensors of the same dimensions and then used to assist a Tucker decomposition in order to achieve data dimensionality reduction. We design two types of clustering models for the tensors: PCA Tensor Clustering model and Non-negative Tensor Clustering model, by utilizing different regularizations. The tensor clustering can thus be solved by the optimization method based on the alternative coordinate scheme. Interestingly, our experiments show that the proposed models yield comparable or even better performance compared to most recent clustering algorithms based on matrix factorization.

Joint multiple dictionary learning for tensor sparse coding

Traditional dictionary learning algorithms are used for finding a sparse representation on high dimensional data by transforming samples into a one-dimensional (1D) vector. This 1D model loses the inherent spatial structure property of data. An alternative solution is to employ Tensor Decomposition for dictionary learning on their original structural form —a tensor— by learning multiple dictionaries along each mode and the corresponding sparse representation in respect to the Kronecker product of these dictionaries. To learn tensor dictionaries along each mode, all the existing methods update each dictionary iteratively in an alternating manner. Because atoms from each mode dictionary jointly make contributions to the sparsity of tensor, existing works ignore atoms correlations between different mode dictionaries by treating each mode dictionary independently. In this paper, we propose a joint multiple dictionary learning method for tensor sparse coding, which explores atom correlations for sparse representation and updates multiple atoms from each mode dictionary simultaneously. In this algorithm, the Frequent-Pattern Tree (FP-tree) mining algorithm is employed to exploit frequent atom patterns in the sparse representation. Inspired by the idea of K-SVD, we develop a new dictionary update method that jointly updates elements in each pattern. Experimental results demonstrate our method outperforms other tensor based dictionary learning algorithms.

Tensor regression based on linked multiway parameter analysis

Classical regression methods take vectors as covariates and estimate the corresponding vectors of regression parameters. When addressing regression problems on covariates of more complex form such as multi-dimensional arrays (i.e. tensors), traditional computational models can be severely compromised by ultrahigh dimensionality as well as complex structure. By exploiting the special structure of tensor covariates, the tensor regression model provides a promising solution to reduce the model’s dimensionality to a manageable level, thus leading to efficient estimation. Most of the existing tensor-based methods independently estimate each individual regression problem based on tensor decomposition which allows the simultaneous projections of an input tensor to more than one direction along each mode. As a matter of fact, multi-dimensional data are collected under the same or very similar conditions, so that data share some common latent components but can also have their own independent parameters for each regression task. Therefore, it is beneficial to analyse regression parameters among all the regressions in a linked way. In this paper, we propose a tensor regression model based on Tucker Decomposition, which identifies not only the common components of parameters across all the regression tasks, but also independent factors contributing to each particular regression task simultaneously. Under this paradigm, the number of independent parameters along each mode is constrained by a sparsity-preserving regulariser. Linked multiway parameter analysis and sparsity modeling further reduce the total number of parameters, with lower memory cost than their tensor-based counterparts. The effectiveness of the new method is demonstrated on real data sets.

Sexual abuse in childhood and postoperative depression in women with breast cancer who opt for immediate reconstruction after mastectomy

INTRODUCTION Breast reconstruction is routinely offered to women who undergo mastectomy for breast cancer. However, patient-reported outcomes are mixed. Child abuse has enduring effects on adults’ well-being and body image. As part of a study into damaging effects of abuse on adjustment to breast cancer, we examined: (i) whether women with history of abuse would be more likely than other women to opt for reconstruction; and (ii) whether mood problems in women opting for reconstruction can be explained by greater prevalence of abuse. PATIENTS AND METHODS We recruited 355 women within 2-4 days after surgery for primary breast cancer; 104 had mastectomy alone and 29 opted for reconstruction. Using standardised questionnaires, women self-reported emotional distress and recollections of childhood sexual abuse. Self-report of distress was repeated 12 months later. RESULTS Women who had reconstruction were younger than those who did not. Controlling for this, they reported greater prevalence of abuse and more distress than those having mastectomy alone. They were also more depressed postoperatively, and this effect remained significant after controlling for abuse. CONCLUSIONS One interpretation of these findings is that history of abuse influences women's decisions about responding to the threat of mastectomy, but it is premature to draw inferences for practice until the findings are replicated. If they are replicated, it will be important to recognise increased vulnerability of some patients who choose reconstruction. Studying the characteristics and needs of women who opt for immediate reconstruction and examining the implications for women's adjustment should be a priority for research.