Characterisation of subglacial water using a constrained transdimensional Bayesian transient electromagnetic inversion

Subglacial water modulates glacier-bed friction and therefore is of fundamental importance when characterising the dynamics of ice masses. The state of subglacial pore water, whether liquid or frozen, is associated with differences in electrical resistivity that span several orders of magnitude; hence, liquid water can be inferred from electrical resistivity depth profiles. Such profiles can be obtained from inversions of transient (time-domain) electromagnetic (TEM) soundings, but these are often non-unique. Here, we adapt an existing Bayesian transdimensional algorithm (Multimodal Layered Transdimensional Inversion – MuLTI) to the inversion of TEM data using independent depth constraints to provide statistical properties and uncertainty analysis of the resistivity profile with depth. The method was applied to ground-based TEM data acquired on the terminus of the Norwegian glacier, Midtdalsbreen, with depth constraints provided by co-located ground-penetrating radar data. Our inversion shows that the glacier bed is directly underlain by material of resistivity 102 Ωm ± 1000 %, with thickness 5–40 m, in turn underlain by a highly conductive basement (100 Ωm ± 15 %). High-resistivity material, 5×104 Ωm ± 25 %, exists at the front of the glacier. All uncertainties are defined by the interquartile range of the posterior resistivity distribution. Combining these resistivity profiles with those from co-located seismic shear-wave velocity inversions to further reduce ambiguity in the hydrogeological interpretation of the subsurface, we propose a new 3-D interpretation in which the Midtdalsbreen subglacial material is partitioned into partially frozen sediment, frozen sediment/permafrost and weathered/fractured bedrock with saline water

Parameterized lower bound and NP-completeness of some HH-free Edge Deletion problems

For a graph $H$, the $H$-free Edge Deletion problem asks whether there exist at most $k$ edges whose deletion from the input graph $G$ results in a graph without any induced copy of $H$. We prove that $H$-free Edge Deletion is NP-complete if $H$ is a graph with at least two edges and $H$ has a component with maximum number of vertices which is a tree or a regular graph. Furthermore, we obtain that these NP-complete problems cannot be solved in parameterized subexponential time, i.e., in time $2^{o(k)}\cdot |G|^{O(1)}$, unless Exponential Time Hypothesis fails.Comment: 15 pages, COCOA 15 accepted pape

Exercise interventions for people undergoing multimodal cancer treatment that includes surgery

This is the protocol for a review and there is no abstract. The objectives are as follows: To determine the effect of exercise interventions for people undergoing multimodal treatment including surgery on physical fitness, safety and feasibility, health-related quality of life and other important health outcomes

Physical activity levels in locally advanced rectal cancer patients following neoadjuvant chemoradiotherapy and an exercise training programme before surgery: a pilot study

Background: The aim of this pilot study was to measure changes in physical activity level (PAL) variables, as well as sleep duration and efficiency in people with locally advanced rectal cancer (1) before and after neoadjuvant chemoradiotherapy (CRT) and (2) after participating in a pre-operative 6-week in-hospital exercise training programme, following neoadjuvant CRT prior to major surgery, compared to a usual care control group.Methods: We prospectively studied 39 consecutive participants (27 males). All participants completed standardised neoadjuvant CRT: 23 undertook a 6-week in-hospital exercise training programme following neoadjuvant CRT. These were compared to 16 contemporaneous non-randomised participants (usual care control group). All participants underwent a continuous 72-h period of PA monitoring by SenseWear biaxial accelerometer at baseline, immediately following neoadjuvant CRT (week 0), and at week 6 (following the exercise training programme).Results: Of 39 recruited participants, 23 out of 23 (exercise) and 10 out of 16 (usual care control) completed the study. In all participants (n = 33), there was a significant reduction from baseline (pre-CRT) to week 0 (post-CRT) in daily step count: median (IQR) 4966 (4435) vs. 3044 (3265); p < 0.0001, active energy expenditure (EE) (kcal): 264 (471) vs. 154 (164); p = 0.003, and metabolic equivalent (MET) (1.3 (0.6) vs. 1.2 (0.3); p = 0.010). There was a significant improvement in sleep efficiency (%) between week 0 and week 6 in the exercise group compared to the usual care control group (80 (13) vs. 78 (15) compared to (69 ((24) vs. 76 (20); p = 0.022), as well as in sleep duration and lying down time (p < 0.05) while those in active EE (kcal) (152 (154) vs. 434 (658) compared to (244 (198) vs. 392 (701) or in MET (1.3 (0.4) vs. 1.5 (0.5) compared to (1.1 (0.2) vs. 1.5 (0.5) were also of importance but did not reach statistical significance (p > 0.05). An apparent improvement in daily step count and overall PAL in the exercise group was not statistically significant.Conclusions: PAL variables, daily step count, EE and MET significantly reduced following neoadjuvant CRT in all participants. A 6-week pre-operative in-hospital exercise training programme improved sleep efficiency, sleep duration and lying down time when compared to participants receiving usual care

Multimodal Layered Transdimensional Inversion of Seismic Dispersion Curves With Depth Constraints

MuLTI (Multimodal Layered Transdimensional Inversion) is a Markov chain Monte Carlo implementation of Bayesian inversion for the probability distribution of shear wave velocity (Vs) as a function of depth. Based on Multichannel Analysis of Surface Wave methods, it requires as data (i) a Rayleigh-wave dispersion curve and (ii) additional layer depth constraints, the latter we show significantly improve resolution compared to conventional unconstrained inversions. Such depth constraints may be drawn from any source (e.g., boreholes, complementary geophysical data) provided they also represent a seismic interface. We apply MuLTI to a Norwegian glacier, Midtdalsbreen, in which ground-penetrating radar was used to constrain internal layers of snow, ice, and subglacial sediments, with transitions at 2 and 25.5 m, and whose Vs is assumed to be in the range 500–1,700, 1,700–1,950, and 200–2,800 m/s, respectively. Synthetic modeling demonstrates that MuLTI recovers the true model of Vs variation with depth. Significantly, compared to inversions without depth constraints, in this synthetic case MuLTI not only reduces by about a factor of 10 the error between the true and the best fitting model, but also reduces by a factor of 2 the vertically averaged spread of the distribution of Vs based on the 95% credible intervals. We further show that using frequencies above about 100 Hz lead to unconverged solutions due to mode ambiguities associated with fine spatial structures. For our acquired data on Midtdalsbreen, we use 14-100 Hz data for which MuLTI produces a large-scale converged inversion

Electrophysiological Correlates of Strategic Monitoring in Event-Based and Time-Based Prospective Memory

Prospective memory (PM) is the ability to remember to accomplish an action when a particular event occurs (i.e., event-based PM), or at a specific time (i.e., time-based PM) while performing an ongoing activity. Strategic Monitoring is one of the basic cognitive functions supporting PM tasks, and involves two mechanisms: a retrieval mode, which consists of maintaining active the intention in memory; and target checking, engaged for verifying the presence of the PM cue in the environment. The present study is aimed at providing the first evidence of event-related potentials (ERPs) associated with time-based PM, and at examining differences and commonalities in the ERPs related to Strategic Monitoring mechanisms between event- and time-based PM tasks

Subglacial sediment distribution from constrained seismic inversion, using MuLTI software: Examples from Midtdalsbreen, Norway

Fast ice flow is associated with the deformation of subglacial sediment. Seismic shear velocities, Vs, increase with the rigidity of material and hence can be used to distinguish soft sediment from hard bedrock substrates. Depth profiles of Vs can be obtained from inversions of Rayleigh wave dispersion curves, from passive or active-sources, but these can be highly ambiguous and lack depth sensitivity. Our novel Bayesian transdimensional algorithm, MuLTI, circumvents these issues by adding independent depth constraints to the inversion, also allowing comprehensive uncertainty analysis. We apply MuLTI to the inversion of a Rayleigh wave dataset, acquired using active-source (Multichannel Analysis of Surface Waves) techniques, to characterise sediment distribution beneath the frontal margin of Midtdalsbreen, an outlet of Norway's Hardangerjøkulen ice cap. Ice thickness (0–20 m) is constrained using co-located GPR data. Outputs from MuLTI suggest that partly-frozen sediment (Vs 500–1000 m s−1), overlying bedrock (Vs 2000–2500 m s−1), is present in patches with a thickness of ~4 m, although this approaches the resolvable limit of our Rayleigh wave frequencies (14–100 Hz). Uncertainties immediately beneath the glacier bed are <280 m s−1, implying that MuLTI cannot only distinguish bedrock and sediment substrates but does so with an accuracy sufficient for resolving variations in sediment properties

Order of Magnitude Smaller Limit on the Electric Dipole Moment of the Electron

The Standard Model of particle physics is known to be incomplete. Extensions to the Standard Model, such as weak-scale supersymmetry, posit the existence of new particles and interactions that are asymmetric under time reversal (T) and nearly always predict a small yet potentially measurable electron electric dipole moment (EDM), d_e, in the range of 10^(−27) to 10^(−30) e·cm. The EDM is an asymmetric charge distribution along the electron spin (S) that is also asymmetric under T. Using the polar molecule thorium monoxide, we measured d_e = (–2.1±3.7_(stat)±2.5_(syst)) × 10−29 e·cm. This corresponds to an upper limit of ❘d_e❘ < 8.7 × 10^(−29) e·cm with 90% confidence, an order of magnitude improvement in sensitivity relative to the previous best limit. Our result constrains T-violating physics at the TeV energy scale