Predictive mapping of reef fish species richness, diversity and biomass in Zanzibar using IKONOS imagery and machine-learning techniques

During the last three decades, the large spatial coverage of remote sensing data has been used in coral reef research to map dominant substrate types, geomorphologic zones, and bathymetry. During the same period, field studies have documented statistical relationships between variables quantifying aspects of the reef habitat and its fish community. Although the results of these studies are ambiguous, some habitat variables have frequently been found to correlate with one or more aspects of the fish community. Several of these habitat variables, including depth, the structural complexity of the substrate, and live coral cover, are possible to estimate with remote sensing data. In this study, we combine a set of statistical and machine-learning models with habitat variables derived from IKONOS data to produce spatially explicit predictions of the species richness, biomass, and diversity of the fish community around two reefs in Zanzibar. In the process, we assess the ability of IKONOS imagery to estimate live coral cover, structural complexity and habitat diversity, and we explore the importance of habitat variables, at a range of spatial scales, in the predictive models using a permutation-based technique. Our findings indicate that structural complexity at a fine spatial scale (∼ 5 to 10 m) is the most important habitat variable in predictive models of fish species richness and diversity, whereas other variables such as depth, habitat diversity, and structural complexity at coarser spatial scales contribute to predictions of biomass. In addition, our results demonstrate that complex model types such as tree-based ensemble techniques provide superior predictive performance compared to the more frequently used linear models, achieving a reduction of the cross-validated root-mean-squared prediction error of 3-11%. Although aerial photographs and airborne lidar instruments have recently been used to produce spatially explicit predictions of reef fish community variables, our study illustrates the possibility of doing so with satellite data. The ability to use satellite data may bring the cost of creating such maps within the reach of both spatial ecology researchers and the wide range of organizations involved in marine spatial planning.     

A GC–MS-based metabonomic investigation of blood serum from irritable bowel syndrome patients undergoing intervention with acidified milk products

In the present study, the use of gas chromatography mass spectrometry (GC–MS)-based metabonomics to characterize blood serum in an intervention study of patients suffering from the common gastrointestinal disorder irritable bowel syndrome (IBS) was investigated. The patients included in the study consumed an acidified milk product with (n = 30) or without probiotics (n = 31) (Lactobacillus paracasei F19, Lactobacillus acidophilus LA-5 and Bifidobacterium lactis BB-12) for an 8-week period, and blood serum samples were collected before and after the intervention. Acidified milk is commonly used as a delivering vector for probiotics in commercial consumer settings. The serum samples were extracted and derivatized using N-Methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA), and GC–MS analysis was carried out. Multivariate data analysis including principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), and S-plot was applied on the obtained GC–MS data, which revealed higher serum lactate, glutamine, proline creatinine/creatine, and aspartic acid levels and lower serum glucose levels after the intervention period for both treatment groups. Consequently, the present study indicated an effect of acidified milk consumption on the plasma metabolite profile, which was independent of a concomitant intake of probiotics. In addition, the present study demonstrates that GC–MS is a useful analytical technique for metabonomics studies of blood serum.     

Prediction of timber bending strength and in-member cross-sectional stiffness variation on the basis of local wood fibre orientation

Machine strength grading of structural timber is based upon relationships between so called indicating properties (IPs) and bending strength. However, such relationships applied on the market today are rather poor. In this paper, new IPs and a new grading method resulting in more precise strength predictions are presented. The local fibre orientation on face and edge surfaces of wooden boards was identified using high resolution laser scanning. In combination with knowledge regarding basic wood material properties for each investigated board, the grain angle information enabled a calculation of the variation of the local MOE in the longitudinal direction of the boards. By integration over cross-sections along the board, an edgewise bending stiffness profile and a longitudinal stiffness profile, respectively, were calculated. A new IP was defined as the lowest bending stiffness determined along the board. For a sample of 105 boards of Norway spruce of dimension 45 × 145 × 3,600 mm³, a coefficient of determination as high as 0.68–0.71 was achieved between this new IP and bending strength. For the same sample, the coefficient of determination between global MOE, based on the first longitudinal resonance frequency and the board density, and strength was only 0.59. Furthermore, it is shown that improved accuracy when determining the stiffness profiles of boards will lead to even better predictions of bending strength. The results thus motivate both an industrial implementation of the suggested method and further research aiming at more accurately determined board stiffness profiles.     

Supercritical wood impregnation

The use of supercritical fluids for delivering biocides into wood and wood composites is an attractive technique because of the high penetration capacity of these solvents compared to the liquids used in conventional treatment methods. During the past two decades supercritical wood impregnation has moved from lab scale to commercial scale.This review presents an overview of the main research efforts that has been carried out within the field of supercritical wood impregnation. Results and conclusions of research within four main categories, i.e. (1) effects of impregnation on physical properties of samples, (2) retention and distribution of biocide in impregnated samples, (3) biological performance of impregnated samples, and (4) mathematical modeling of supercritical impregnation are reviewed and discussed.     

Detection of polyunsaturated omega-6 fatty acid in human malignant prostate tissue by 1D and 2D high-resolution magic angle spinning NMR spectroscopy

Object  

Polyunsaturated omega-6 fatty acids (PUFAs) have been shown to promote prostate cancer. Here, we describe the use of HRMAS NMR spectroscopy to detect omega-6 PUFA species in prostate tissues.     

Phase Diffusion and Suppression of the Supercurrent by Quantum-Mechanical Fluctuations of the Josephson Plasma at Small Superconducting Point Contacts

The RCSJ model of resistively and capacitively shunted Josephson junctions is used to describe superconducting point contacts over a wide range of resistances up to the metallic–tunneling transition. Their small dynamic capacitance of order C = 0.1 fF due to the point-contact geometry results in a huge plasma frequency. The critical current is then strongly suppressed and the contact resistance becomes finite because of quantum-mechanical zero-point fluctuations of the Josephson plasma and the rather large escape rate out of the zero-voltage state due to quantum tunneling. We test the predictions of the RCSJ model on the classical superconductors lead, indium, aluminum, and cadmium.     

Cable crossings-derating considerations. I. Derivation of deratingequations

Dangerously high interference temperatures can occur at points where cables cross external heat sources even when the crossing occurs at 90°. For perpendicular and oblique crossings, these interference temperatures are usually ignored for distribution circuits, whereas for transmission cables, corrective actions in physical installation condition are sometimes taken. Analytical solutions are almost never used to determine the effect of external heat source on the ampacity of the rated cable. The main reason no computations are performed is an absence of either derating formulas or derating tables (curves) and not the lack of a need. To fill this gap, an analytical solution for the computation of the derating factors has been developed and is presented in this paper. The solution is simple and accurate enough to be suitable for standardization purposes. A numerical example involving the intersection of a pipe-type cable by a distribution circuit is presented to show the effect of perpendicular and oblique crossings on the ampacity of both circuits. In this practical example, the ampacity of the pipe-type cable is significantly affected for a range of crossing angles. A conservative practice, used by many utilities in cases like this, would be to assume that the cables are parallel. However, in our example for a 90° crossing, such an approach would unnecessarily decreases the ampacity of the pipe-type cable by almost 20%     

Learners as Knowledge Workers—Some Implications*

Traditionally, behavioristic models have been used for the design of interactive learning environments. In contrast, this paper proposes a pedagogical model based on social constructionism and phenomenology which we believe is more adequate when, for instance, information seeking and WWW become natural components in the learning situation. In this model, learners are seen as persons who continuously alter their conceptions and ideas by working with data, information, and knowledge, i.e. learners as knowledge workers. The most important point in viewing learners as knowledge workers is exactly that the learners change their understanding by working with the information, and that they do that with the help of cognitive tools. I see it as a necessity that the learning environment consists of tools that support them in their learning processes: tools for constructing, processing and observing information, data, and knowledge. Equally important in this new kind of learning situation are tools to establish and maintain focus, manage information overload, to bridge distances in the learning situation, and to communicate.