Prograded Holocene beach-ridges with superimposed dunes in north-east Ireland: mechanisms and timescales of fine and coarse beach sediment decoupling and deposition

Two depositional models to account for Holocene gravel-dominated beach ridges covered by dunes, occurring on the northern coast of Ireland, are considered in the light of infrared-stimulated luminescence ages of sand units within beach ridges, and 14C ages from organic horizons in dunes. A new chronostratigraphy obtained from prograded beach ridges with covering dunes at Murlough, north-east Ireland, supports a model of mesoscale alternating sediment decoupling (ASD) on the upper beach, rather than macroscale sequential sediment sourcing to account for prograded beach ridges and covering dunes. The ASD model specifies storm or fair-weather sand beach ridges forming at high-tide positions (on an annual basis at minimum), which acted as deflationary sources for landward foredune development. Only a limited number of such late-Holocene beach ridges survive in the observed prograded series. Beach ridges only survive when capped by storm-generated gravel beaches that are deposited on a mesoscale time spacing of 50–130 years. The morphodynamic shift from a dissipative beach face for dune formation to a reflective beach face for gravel capping appears to be controlled by the beach sand volume falling to a level where reflective conditions can prevail. Sediment volume entering the beach is thought to have fluctuated as a function of a forced regression associated with the falling sea level from the mid-Holocene highstand (ca. 6000 cal. yr BP) identified in north-east Ireland. The prograded beach ridges dated at ca. 3000 to 2000 cal. yr BP indicate that the Holocene highstand’s regressive phase may have lasted longer than previously specified.

Numerical ‘health check’ for scientific codes: the CADNA approach

Scientific computation has unavoidable approximations built into its very fabric. One important source of error that is difficult to detect and control is round-off error propagation which originates from the use of finite precision arithmetic. We propose that there is a need to perform regular numerical `health checks' on scientific codes in order to detect the cancerous effect of round-off error propagation. This is particularly important in scientific codes that are built on legacy software. We advocate the use of the CADNA library as a suitable numerical screening tool. We present a case study to illustrate the practical use of CADNA in scientific codes that are of interest to the Computer Physics Communications readership. In doing so we hope to stimulate a greater awareness of round-off error propagation and present a practical means by which it can be analyzed and managed.

2DRMP: A suite of two-dimensional R-matrix propagation codes

The R-matrix method has proved to be a remarkably stable, robust and efficient technique for solving the close-coupling equations that arise in electron and photon collisions with atoms, ions and molecules. During the last thirty-four years a series of related R-matrix program packages have been published periodically in CPC. These packages are primarily concerned with low-energy scattering where the incident energy is insufficient to ionize the target. In this paper we describe previous term2DRMP,next term a suite of two-dimensional R-matrix propagation programs aimed at creating virtual experiments on high performance and grid architectures to enable the study of electron scattering from H-like atoms and ions at intermediate energies.

Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.

Superimposed vibration confers no additional benefit compared with resistance training alone

Eighteen participants (22-43 years) were randomly allocated to one of two groups: resistance training combined with vibration (VIB; five males, four females) or resistance training alone (CON; five males, four females). Each participant trained three sessions per week (three sets of 10 seated calf raises against a load, which was increased progressively from 75% of one repetition maximum (1RM) to 90% 1RM for 4 weeks. For the VIB group, a vibratory stimulus (30 Hz, 2.5 mm amplitude) was applied to the soles of the feet by a vibration platform. The two groups did not differ significantly with respect to the total amount of work performed during training. Both groups showed a significant increase in maximum voluntary contraction and 1RM (P