Review : "Quality of life: the assessment, analysis and interpretation of patient-reported outcomes (2nd Ed.)" by Peter M. Fayers & David Machin

An updated version, this excellent text is a timely addition to the library of any nurse researching in oncology or other settings where individuals’ quality of life must be understood. Health-related quality of life should be a central aspect of studies concerned with health and illness. Indeed, considerable evidence has recently emerged in oncology and other research settings that selfreported quality of life is of great prognostic significance and may be the most reliable predictor of subsequent morbidity and mortality. From a nursing perspective, it is also gratifying to note that novel therapy and other oncology studies increasingly recognize the importance of understanding patients’ subjective experiences of an intervention over time and to ascertain whether patients perceive that a new intervention makes a difference to their quality of life and treatment outcomes. Measurements of quality of life are now routine in clinical trials of chemotherapy drugs and are often considered the prime outcome of interest in the cost/benefit analyses of these treatments. The authors have extensive experience in qualityof- life assessment in cancer clinical trials, where most of the pioneering work into quality of life has been conducted. That said, many of the health-related qualityof- life issues discussed are common to many illnesses, and researchers outside of cancer should find the book equally helpful.

Measurement and Interpretation of Salinity Tolerance in Four Perennial Grasses

Whilst the topic of soil salinity has received a substantive research effort over the years, the accurate measurement and interpretation of salinity tolerance data remain problematic. The tolerance of four perennial grass species (non-halophytes) to sodium chloride (NaCl) dominated salinity was determined in a free-flowing sand culture system. Although the salinity tolerance of non-halophytes is often represented by the threshold salinity model (bent-stick model), none of the species in the current study displayed any observable salinity threshold. Further, the observed yield decrease was not linear as suggested by the model. On re-examination of earlier datasets, we conclude that the threshold salinity model does not adequately describe the physiological processes limiting growth of non-halophytes in saline soils. Therefore, the use of the threshold salinity model is not recommended for non-halophytes, but rather, a model which more accurately reflects the physiological response observed in these saline soils, such as an exponential regression curve.

A new class of separators and planarity of chordal graphs

We introduce a new class of clique separators, called base sets, for chordal graphs. Base sets of a chordal graph closely reflect its structure. We show that the notion of base sets leads to structural characterizations of planar k-trees and planar chordal graphs. Using these characterizations, we develop linear time algorithms for recognizing planar k-trees and planar chordal graphs. These algorithms are extensions of the Lexicographic_Breadth_First_Search algorithm for recognizing chordal graphs and are much simpler than the general planarity checking algorithm. Further, we use the notion of base sets to prove the equivalence of hamiltonian 2-trees and maximal outerplanar graphs.

Biphenyl ethers conjugated CdSe/ZnS core/shell quantum dots and interpretation of the mechanism of amyloid fibril disruption

The biphenyl ethers (BPEs) are the potent inhibitors of TTR fibril formation and are efficient fibril disrupter. However, the mechanism by which the fibril disruption occurs is yet to be fully elucidated. To gain insight into the mechanism, we synthesized and used a new QD labeled BPE to track the process of fibril disruption. Our studies showed that the new BPE-QDs bind to the fiber uniformly and has affinity and specificity for TTR fiber and disrupted the pre-formed fiber at a relatively slow rate. Based on these studies we put forth the probable mechanism of fiber disruption by BPEs. Also, we show here that the BPE-QDs interact with high affinity to the amyloids of A beta(42), lysozyme and insulin. The potential of BPE-QDs in the detection of senile plaque in the brain of transgenic Alzheimer's mice has also been explored. (C) 2010 Elsevier Ltd. All rights reserved.

Demixing of severely overlapped H-1 NMR resonances and interpretation of anomalous intensity pattern of dipolar coupled A(3) spins in a weakly aligning medium

We report a single C-13 spin edited selective proton-proton correlation experiment to decipher overcrowded 13C coupled proton NMR spectra of weakly dipolar coupled spin systems. The experiment unravels the masked C-13 satellites in proton spectrum and permits the measurement of one bond carbon-proton residual dipolar couplings in I3S and for each diastereotopic proton in I2S groups. It also provides all the possible homonuclear proton-proton residual couplings which are otherwise difficult to extract from the broad and featureless one dimensional H-1 spectrum, in addition to enantiodifferentiation in a chiral molecule. Employment of heteronuclear (C-13) decoupling in the evolution period results in complete demixing of overlapped signals from enantiomers. The observed anomalous intensity pattern in strongly dipolar coupled methyl protons in methyl selective correlation experiment has been interpreted using polarization operator formalism. (C) 2010 Elsevier Inc. All rights reserved.

Development and Evaluation of Statistical Downscaling Models for Monthly Precipitation

Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies.

Challenges in the quantification and interpretation of spike-LFP relationships

Brain signals often show fluctuations in particular frequency bands, which are highly conserved across species and are associated with specific behavioural states. Such rhythmic patterns can be captured in the local field potential (LFP), which is obtained by low-pass filtering the extracellular signal recorded from microelectrodes. However, LFP also captures other neural processes that are associated with spikes, such as synaptic events preceding a spike, low-frequency component of the action potential (spike bleed-through'') and spike afterhyperpolarization, which pose difficulties in the estimation of the amplitude and phase of the rhythm with respect to spikes. Here we discuss these issues and different techniques that have been used to dissociate the rhythm from other neural events in the LFP.

Boxicity and cubicity of product graphs

The boxicity (cubicity) of a graph G is the minimum natural number k such that G can be represented as an intersection graph of axis-parallel rectangular boxes (axis-parallel unit cubes) in R-k. In this article, we give estimates on the boxicity and the cubicity of Cartesian, strong and direct products of graphs in terms of invariants of the component graphs. In particular, we study the growth, as a function of d, of the boxicity and the cubicity of the dth power of a graph with respect to the three products. Among others, we show a surprising result that the boxicity and the cubicity of the dth Cartesian power of any given finite graph is, respectively, in O(log d/ log log d) and circle dot(d/ log d). On the other hand, we show that there cannot exist any sublinear bound on the growth of the boxicity of powers of a general graph with respect to strong and direct products. (C) 2015 Elsevier Ltd. All rights reserved.

Asymptotic behavior and interpretation of virtual states: The effects of confinement and of basis sets

A real-space high order finite difference method is used to analyze the effect of spherical domain size on the Hartree-Fock (and density functional theory) virtual eigenstates. We show the domain size dependence of both positive and negative virtual eigenvalues of the Hartree-Fock equations for small molecules. We demonstrate that positive states behave like a particle in spherical well and show how they approach zero. For the negative eigenstates, we show that large domains are needed to get the correct eigenvalues. We compare our results to those of Gaussian basis sets and draw some conclusions for real-space, basis-sets, and plane-waves calculations. (C) 2016 AIP Publishing LLC.

Observation and interpretation of tectonic strain release mechanisms

In four chapters various aspects of earthquake source are studied.

Chapter I

Surface displacements that followed the Parkfield, 1966, earthquakes were measured for two years with six small-scale geodetic networks straddling the fault trace. The logarithmic rate and the periodic nature of the creep displacement recorded on a strain meter made it possible to predict creep episodes on the San Andreas fault. Some individual earthquakes were related directly to surface displacement, while in general, slow creep and aftershock activity were found to occur independently. The Parkfield earthquake is interpreted as a buried dislocation.

Chapter II

The source parameters of earthquakes between magnitude 1 and 6 were studied using field observations, fault plane solutions, and surface wave and S-wave spectral analysis. The seismic moment, M_O, was found to be related to local magnitude, M_L, by log M_O = 1.7 M_L + 15.1. The source length vs magnitude relation for the San Andreas system found to be: M_L = 1.9 log L - 6.7. The surface wave envelope parameter AR gives the moment according to log M_O = log AR₃₀₀ + 30.1, and the stress drop, τ, was found to be related to the magnitude by τ = 0.54 M - 2.58. The relation between surface wave magnitude M_S and M_L is proposed to be M_S = 1.7 M_L - 4.1. It is proposed to estimate the relative stress level (and possibly the strength) of a source-region by the amplitude ratio of high-frequency to low-frequency waves. An apparent stress map for Southern California is presented.

Chapter III

Seismic triggering and seismic shaking are proposed as two closely related mechanisms of strain release which explain observations of the character of the P wave generated by the Alaskan earthquake of 1964, and distant fault slippage observed after the Borrego Mountain, California earthquake of 1968. The Alaska, 1964, earthquake is shown to be adequately described as a series of individual rupture events. The first of these events had a body wave magnitude of 6.6 and is considered to have initiated or triggered the whole sequence. The propagation velocity of the disturbance is estimated to be 3.5 km/sec. On the basis of circumstantial evidence it is proposed that the Borrego Mountain, 1968, earthquake caused release of tectonic strain along three active faults at distances of 45 to 75 km from the epicenter. It is suggested that this mechanism of strain release is best described as "seismic shaking."

Chapter IV

The changes of apparent stress with depth are studied in the South American deep seismic zone. For shallow earthquakes the apparent stress is 20 bars on the average, the same as for earthquakes in the Aleutians and on Oceanic Ridges. At depths between 50 and 150 km the apparent stresses are relatively high, approximately 380 bars, and around 600 km depth they are again near 20 bars. The seismic efficiency is estimated to be 0.1. This suggests that the true stress is obtained by multiplying the apparent stress by ten. The variation of apparent stress with depth is explained in terms of the hypothesis of ocean floor consumption.