Reconstruction of Two-Dimensional Spectra from One-Dimensional Projections-Examples from Solid State NMR

The use of Projection Reconstruction (PR) to obtain two-dimensional (2D) spectra from one-dimensional (1D) data in the solid state is illustrated. The method exploits multiple 1D spectra obtained using magic angle spinning and off-magic angle spinning. The spectra recorded under the influence of scaled heteronuclear scalar and dipolar couplings in the presence of homonuclear dipolar decoupling sequences have been used to reconstruct J/D Resolved 2D-NMR spectra. The use of just two 1D spectra is observed sufficient to reconstruct a J-resolved 2D-spectrum while a Separated Local Field (SLF) 2D-NMR spectrum could be obtained from three 1D spectra. The experimental techniques for recording the 10 spectra and procedure of reconstruction are discussed and the reconstructed results are compared with 20 experiments recorded in traditional methods. The application of the technique has been made to a solid polycrystalline sample and to a uniaxially oriented liquid crystal. Implementation of PR-NMR in solid state provides high-resolution spectra as well as leads to significant reduction in experimental time. The experiments are relatively simple and are devoid of several technical complications involved in performing the 2D experiments.

Challenges in using science-based shoreline setbacks: Examples from South Carolina

Beachfront jurisdictional lines were established by the South Carolina Beachfront Management Act (SC Code §48- 39-250 et seq.) in 1988 to regulate the new construction, repair, or reconstruction of buildings and erosion control structures along the state’s ocean shorelines. Building within the state’s beachfront “setback area” is allowed, but is subject to special regulations. For “standard beaches” (those not influenced by tidal inlets or associated shoals), a baseline is established at the crest of the primary oceanfront sand dune; for “unstabilized inlet zones,” the baseline is drawn at the most landward point of erosion during the past forty years. The parallel setback line is then established landward of the baseline a distance of forty times the long-term average annual erosion rate (not less than twenty feet from the baseline in stable or accreting areas). The positions of the baseline and setback line are updated every 8-10 years using the best available scientific and historical data, including aerial imagery, LiDAR, historical shorelines, beach profiles, and long-term erosion rates. One advantage of science-based setbacks is that, by using actual historical and current shoreline positions and beach profile data, they reflect the general erosion threat to beachfront structures. However, recent experiences with revising the baseline and setback line indicate that significant challenges and management implications also exist. (PDF contains 3 pages)

Shoal manipulation as an effective solution to site specific beach management, examples from three South Carolina beaches

Soft engineering solutions are the current standard for addressing coastal erosion in the US. In South Carolina, beach nourishment from offshore sand deposits and navigation channels has mostly replaced construction of seawalls and groins, which were common occurrences in earlier decades. Soft engineering solutions typically provide a more natural product than hard solutions, and also eliminate negative impacts to adjacent areas which are often associated with hard solutions. A soft engineering solution which may be underutilized in certain areas is shoal manipulation. (PDF contains 4 pages)

On the optimal usage of labelled examples in semi-supervised multi-class classification problems

In recent years, the performance of semi-supervised learning has been theoretically investigated. However, most of this theoretical development has focussed on binary classification problems. In this paper, we take it a step further by extending the work of Castelli and Cover [1] [2] to the multi-class paradigm. Particularly, we consider the key problem in semi-supervised learning of classifying an unseen instance x into one of K different classes, using a training dataset sampled from a mixture density distribution and composed of l labelled records and u unlabelled examples. Even under the assumption of identifiability of the mixture and having infinite unlabelled examples, labelled records are needed to determine the K decision regions. Therefore, in this paper, we first investigate the minimum number of labelled examples needed to accomplish that task. Then, we propose an optimal multi-class learning algorithm which is a generalisation of the optimal procedure proposed in the literature for binary problems. Finally, we make use of this generalisation to study the probability of error when the binary class constraint is relaxed.

River salinity variations in response to discharge: examples from the western United States during the early 1900s

Major controls on river salinity (total dissolved solids) in the western United States are climate, geology, and human activity. Climate, in general, influences soil-river salinity via salt-balance variations. When climate becomes wetter, river discharge increases and soil-river salinity decreases; when climate becomes drier river discharge decreases and soil-river salinity increases. This study characterizes the river salinity response to discharge using statistical-dynamic methods. An exploratory analysis of river salinity, using early 1900s water quality surveys in the western United States, shows much river salinity variability is in response to storm and annual discharge. Presumably this is because river discharge is largely supported by surface flow.

TWO TUTORIAL EXAMPLES OF MULTIVARIABLE CONTROL SYSTEM DESIGN.

Two tutorial examples are presented which illustrate different methods of designing practical multivariable control systems using frequency-domain techniques. In the first case eigenvector alignment techniques are used to manipulate and shape the generalized Nyquist diagrams, while in the second case LQG theory in conjunction with singular value plots is employed. In both cases the designs are carried out on a modern computer-aided control-system design package.