An ecologically useful classification of mean and near-bed flows in streams and rivers

SUMMARY. 1. Mean motion and near-bed flows in streams and rivers can be described using a classification derived from fairly simple field measurements. Our proposed classification is ecologically useful because it incorporates the combined effects of velocity, depth and substrate roughness to provide a means of quantifying the flow regimes occurring within the microhabitats of stream benthos. 2. Mean motion is characterized by the Reynolds number and the Froude number. Both are easily calculated, and because they are dimensionless they provide a means of comparing flows at different sites. 3. Five categories of near-bed flows (i.e. the flow microenvironments of stream benthos) are recognized. Flow may be hydraulically smooth or hydraulically rough and the latter category is subdivided further into: chaotic flow, wake interference flow, isolated roughness flow and skimming flow. Hydraulically smooth flows occur in sections of a river bed with fine sediments (e.g. sands, muds and clays). over flat sheets of bedrock, or in association with the flat blades of submerged macrophytes. Hydraulically rough flows occur where the substrate elements are larger (e. g. pebbles, cobbles and boulders) and are a function of substrate roughness and the depth of flow relative to the height of the roughness elements. Chaotic flows and wake interference flows predominate in riffles whilst isolated roughness flows and skimming flows are more likely to be a feature of runs. 4. Conventional stream sampling methods (e.g. the Surber and box or cylinder samplers) may collect across several different flow microhabitats. Our classification should enable different flow microenvironments to be recognized and so sampled more appropriately which, in turn, may reduce apparent clumping and the wide confidence intervals of benthic population estimates. Because our classification identifies ‘patches’ within the flow regime associated with the stream bed it enables stream ecologists to generate testable hypotheses regarding the distribution and abundance of benthic species in response to flow. 5. Our classification identifies spatial patterns in the flow regimes associated with the stream bed. Temporal patterns have not been identified: however, predictable changes in spatial patterns will resuh from temporal changes in stream discharge.     

Adaptation to natural flow regimes

Floods and droughts are important features of most running water ecosystems, but the alteration of natural flow regimes by recent human activities, such as dam building, raises questions related to both evolution and conservation. Among organisms inhabiting running waters, what adaptations exist for surviving floods and droughts? How will the alteration of the frequency, timing and duration of flow extremes affect flood- and drought-adapted organisms? How rapidly can populations evolve in response to altered flow regimes? Here, we identify three modes of adaptation (life history, behavioral and morphological) that plants and animals use to survive floods and/or droughts. The mode of adaptation that an organism has determines its vulnerability to different kinds of flow regime alteration. The rate of evolution in response to flow regime alteration remains an open question. Because humans have now altered the flow regimes of most rivers and many streams, understanding the link between fitness and flow regime is crucial for the effective management and restoration of running water ecosystems.     

Influence of submerged macrophytes on sediment composition and near-bed flow in lowland streams

1. Submerged macrophytes have important physical and structural effects on lowland streams. This study investigated the ability of submerged macrophytes to modify the near-bed flow and to retain mineral and organic particles in patches of four common macrophytes in shallow Danish streams during mid-summer. 2. In dense patches of Callitriche cophocarpa and Elodea canadensis, where near-bed velocity was reduced, the sediment surface was markedly raised and enriched with fine particles. In dense patches of Ranunculus peltatus, fine sediments were deposited among rooted shoots in the upstream part of the patches, while erosion and coarse sediments prevailed in the downstream part of the patches because of the strong vortices that formed at the rear and moved up under the trailing canopy. The open canopy of Sparganium emersum, with its streamlined leaves, had little effect on flow and sediment. 3. Patterns of sediment deposition and composition were closely related to the morphology and canopy structure of plant species and the presence of low velocity above the sediment among the rooted shoots. The mineral particles retained probably originate from bed-load, and the enrichment with finer particles within the patches probably results mainly from size-selective processes during erosion and transport of particles rather than during deposition. The mixed sediment composition within patches suggests that the flow-resistant shoots generate an environment conducive to deposition of all transported particles. 4. Fine sediments within macrophyte beds contained high concentrations of organic matter, carbon, nitrogen and phosphorus. The wide scatter in the relationships between mineral grain size and the content of organic matter and nutrients reflects the spatial and temporal complexity of erosion, transport and sedimentation of mineral and organic particles. 5. Enrichment of sediment within macrophyte beds relative to the surrounding substratum ranged from 780 g organic matter m^–2, 30 g N m^–2 and 25 g P m^–2 for the flow-resistant dense canopies af Callitriche cophocarpa to 150 g organic matter m^–2, 6.6 g N m^–2 and 3.4 g P m^–2 for the open canopies of Sparganium emersum. Retention of nutrient-rich particles within the macrophyte beds is probably of limited importance for plant growth in most lowland European streams, because macrophyte growth is rarely nutrient limited.     

New techniques for DNA sequence classification.

DNA sequence classification is the activity of determining whether or not an unlabeled sequence S belongs to an existing class C. This paper proposes two new techniques for DNA sequence classification. The first technique works by comparing the unlabeled sequence S with a group of active motifs discovered from the elements of C and by distinction with elements outside of C. The second technique generates and matches gapped fingerprints of S with elements of C. Experimental results obtained by running these algorithms on long and well conserved Alu sequences demonstrate the good performance of the presented methods compared with FASTA. When applied to less conserved and relatively short functional sites such as splice-junctions, a variation of the second technique combining fingerprinting with consensus sequence analysis gives better results than the current classifiers employing text compression and machine learning algorithms.     

Supervised machine learning techniques for the classification of metabolic disorders in newborns

MOTIVATION: During the Bavarian newborn screening programme all newborns have been tested for about 20 inherited metabolic disorders. Owing to the amount and complexity of the generated experimental data, machine learning techniques provide a promising approach to investigate novel patterns in high-dimensional metabolic data which form the source for constructing classification rules with high discriminatory power. RESULTS: Six machine learning techniques have been investigated for their classification accuracy focusing on two metabolic disorders, phenylketo nuria (PKU) and medium-chain acyl-CoA dehydrogenase deficiency (MCADD). Logistic regression analysis led to superior classification rules (sensitivity >96.8%, specificity >99.98%) compared to all investigated algorithms. Including novel constellations of metabolites into the models, the positive predictive value could be strongly increased (PKU 71.9% versus 16.2%, MCADD 88.4% versus 54.6% compared to the established diagnostic markers). Our results clearly prove that the mined data confirm the known and indicate some novel metabolic patterns which may contribute to a better understanding of newborn metabolism.     

Predictability of phenotypic differentiation across flow regimes in fishes

Fish inhabit environments greatly varying in intensity of water velocity, and these flow regimes are generally believed to be of major evolutionary significance. To what extent does water flow drive repeatable and predictable phenotypic differentiation? Although many investigators have examined phenotypic variation across flow gradients in fishes, no clear consensus regarding the nature of water velocity's effects on phenotypic diversity has yet emerged. Here, I describe a generalized model that produces testable hypotheses of morphological and locomotor differentiation between flow regimes in fishes. The model combines biomechanical information (describing how fish morphology determines locomotor abilities) with ecological information (describing how locomotor performance influences fitness) to yield predictions of divergent natural selection and phenotypic differentiation between low-flow and high-flow environments. To test the model's predictions of phenotypic differentiation, I synthesized the existing literature and conducted a meta-analysis. Based on results gathered from 80 studies, providing 115 tests of predictions, the model produced some accurate results across both intraspecific and interspecific scales, as differences in body shape, caudal fin shape, and steady-swimming performance strongly matched predictions. These results suggest that water flow drives predictable phenotypic variation in disparate groups of fish based on a common, generalized model, and that microevolutionary processes might often scale up to generate broader, interspecific patterns. However, too few studies have examined differentiation in body stiffness, muscle architecture, or unsteady-swimming performance to draw clear conclusions for those traits. The analysis revealed that, at the intraspecific scale, both genetic divergence and phenotypic plasticity play important roles in phenotypic differentiation across flow regimes, but we do not yet know the relative importance of these two sources of phenotypic variation. Moreover, while major patterns within and between species were predictable, we have little direct evidence regarding the role of water flow in driving speciation or generating broad, macroevolutionary patterns, as too few studies have addressed these topics or conducted analyses within a phylogenetic framework. Thus, flow regime does indeed drive some predictable phenotypic outcomes, but many questions remain unanswered. This study establishes a general model for predicting phenotypic differentiation across flow regimes in fishes, and should help guide future studies in fruitful directions, thereby enhancing our understanding of the predictability of phenotypic variation in nature.     

Evolutionary responses of aquatic macroinvertebrates to two contrasting flow regimes

Hydrobiologia - Natural disturbances are agents of natural selection that drive multiple biological adaptations along evolutionary time. Frequent, high magnitude disturbances are expected to select...     

Parameterization and classification of the protein universe via geometric techniques

We present a scheme for the classification of 3487 non-redundant protein structures into 1207 non-hierarchical clusters by using recurring structural patterns of three to six amino acids as keys of classification. This results in several signature patterns, which seem to decide membership of a protein in a functional category. The patterns provide clues to the key residues involved in functional sites as well as in protein-protein interaction. The discovered patterns include a "glutamate double bridge" of superoxide dismutase, the functional interface of the serine protease and inhibitor, interface of homo/hetero dimers, and functional sites of several enzyme families. We use geometric invariants to decide superimposability of structural patterns. This allows the parameterization of patterns and discovery of recurring patterns via clustering. The geometric invariant-based approach eliminates the computationally explosive step of pair-wise comparison of structures. The results provide a vast resource for the biologists for experimental validation of the proposed functional sites, and for the design of synthetic enzymes, inhibitors and drugs.     

Feasibility study of stain-free classification of cell apoptosis based on diffraction imaging flow cytometry and supervised machine learning techniques

This study was to explore the feasibility of prediction and classification of cells in different stages of apoptosis with a stain-free method based on diffraction images and supervised machine learning. Apoptosis was induced in human chronic myelogenous leukemia K562 cells by cis-platinum (DDP). A newly developed technique of polarization diffraction imaging flow cytometry (p-DIFC) was performed to acquire diffraction images of the cells in three different statuses (viable, early apoptotic and late apoptotic/necrotic) after cell separation through fluorescence activated cell sorting with Annexin V-PE and SYTOX® Green double staining. The texture features of the diffraction images were extracted with in-house software based on the Gray-level co-occurrence matrix algorithm to generate datasets for cell classification with supervised machine learning method. Therefore, this new method has been verified in hydrogen peroxide induced apoptosis model of HL-60. Results show that accuracy of higher than 90% was achieved respectively in independent test datasets from each cell type based on logistic regression with ridge estimators, which indicated that p-DIFC system has a great potential in predicting and classifying cells in different stages of apoptosis.     

Shape variation in a benthic stream fish across flow regimes

Evolution of fish body shapes in flowing and non-flowing waters have been examined for several species. Flowing water can select for fish body shapes that increase steady swimming efficiency, whereas non-flowing water can favor shapes that increase unsteady swimming efficiency. Benthic stream fishes often use areas near the substrate that exhibit reduced or turbulent flow, thus it is unclear which swimming forms would be favored in such environments, and how shape might change across flow regimes. To test the relationship between fish body shape and flow regime in a benthic stream fish, we used geometric morphometric techniques to characterize lateral body shape in mountain sucker (Catostomus platyrhynchus) across flow rates, using stream gradient as an indicator of stream flow. Mountain suckers from low-flow environments were more streamlined, consistent with steady swimming body shapes, whereas mountain suckers from high flows had deeper bodies, consistent with unsteady swimming body shapes. In addition, smaller individuals tended to have more robust body shapes. These patterns are opposite to those predicted for stream fishes in the mid-water column. The benthic stream environment represents a distinct selective environment for fish shape that does not appear to conform to the simple dichotomy of flowing versus non-flowing water.     

Field techniques for assessing the reaction of winter wheat cultivars to Septoria nodorum

Methods of assessing the reaction of winter wheat cultivars to Septoria nodorum were compared in nine field trials. Plots were inoculated either by scattering naturally infected wheat debris or by spraying with a suspension of conidia at different growth stages, and were subsequently kept damp by several methods. Disease development was monitored by assessing the percentage cover of different organs by lesions, or by measuring the maximum height of lesions above ground. Major differences between cultivars were evident with all methods of inoculation and assessment, but time of assessment was critical for best differentiation. Inoculation with conidia soon after ear emergence, followed by assessment of lesions on flag leaves and ears, was a simple and effective method. Yield loss due to disease was measured by making comparisons either between inoculated and uninoculated plots, with various degrees of separation, or between inoculated plots with and without fungicidal treatment: the first of these methods was more effective in maintaining a disease differential. Yield loss was positively correlated with severity of disease and there was little evidence that cultivars differed in tolerance of disease. Disease was measured more easily and with less error than yield loss.     

Ultrasound techniques for measurement of blood flow and tissue motion

This article will review the ability of ultrasound techniques to provide 3D information on arterial geometry, blood flow and tissue motion.3D systems. 3D datasets can be obtained by sequential acquisition of 2D slices. Ideally a transducer is required in which there is full control of beam steering within a 3D volume. This requires a 2D array consisting of several thousand elements. Prototype 2D arrays have been built which provide several 3D datasets per second.Blood velocity measurement. Current Doppler systems estimate only the component of velocity in the direction of the Doppler beam. Lack of knowledge of the direction of blood motion and also other effects associated with 'spectral broadening' limit the accuracy of velocity measurement. Improved accuracy can be obtained using vector Doppler systems using 2 or 3 beam directions; this approach is referred to as 'vector Doppler'.Tissue motion. Doppler techniques can also be used to detect tissue motion (Tissue Doppler Imaging or TDI). Motion of the artery wall can be calculated from the TDI images. It is possible to estimate simultaneously motion for adjacent diameters within the longitudinal plane, and to visualise the relative motion at different parts of the wall.     

Alternative regimes for harvesting the seabed

Scott Allen and John P. Craven, editors, Alternatives in Deepsea Mining, Proceedings, Law of the Sea Institute Workshop, December 11–14, 1978, Ka'u Hawaii (Honolulu: Law of the Sea Institute, University of Hawaii, 1979), vii + 110 pp., $12.50.

Jack N. Barkenbus, Deep Seabed Resources: Politics and Technology (New York: The Free Press, 1979), xiv + 191 pp., $14.95.

Ross D. Eckert, The Enclosure of Ocean Resources: Economics and the Law of the Sea (Stanford: Hoover Institution Press, Stanford University, 1979), xiv + 390 pp., $16.95.

I. G. Bulkley, Who Gains From Deep Ocean Mining? Simulating the Impact of Regimes for Regulating Nodule Exploitation, Research Series No. 40 (Berkeley: Institute of International Studies, University of California, 1979), vii + 117 pp., $3.50 (paper).

Judith T. Kildow, editor, Deepsea Mining (Cambridge, MA: The MIT Press, 1980), vii + 110 pp., $2.50.     

Morphometric, densitometric and flow cytometric criteria for the automated classification of thyroid lesions

An automated classification of 73 thyroid lesions using a logical and mathematical approach was attempted. Densitometric, morphometric and flow cytometric parameters were used in Fisher linear discriminant functions to separate goiters or normal thyroids from adenomas and from carcinomas; the combination of this approach with binary discrimination improved the initial classification to a final efficiency of 81%. This approach, which is useful for classifying individual cells, was thus insufficient for classifying these cases. Analysis of the individual parameters showed that thyroid lesions were mainly in the near-diploid region. Two G0G1 populations were present in both benign and malignant lesions and were particularly frequent (50%) in atypical invasive follicular adenomas, probably related to the additional presence of an invasive clone. Near-triploid peaks were associated with malignancy as well as with high proliferative indexes. Nuclear and nucleolar sizes were larger in carcinomas; however, the percentage of the nucleolar area in the nucleus was greater in adenomas and nodular adenomatous goiters. A corrected staining index correlated with the nuclear size and the ploidy of abnormal cells (r = .50), being higher in malignant lesions.     

Development of SVM based classification techniques for the delineation of wave components in 12-lead electrocardiogram

The automatic detection of electrocardiogram (ECG) waves namely P, QRS and T-wave is important to cardiac disease diagnosis. This paper presents an application of support vector machine (SVM) as a classifier for the delineation of ECG wave components in the 12-lead ECG signal. Digital filtering techniques are used to remove power line interference and baseline wander present in the ECG signal. Gradient of the filtered ECG signal is used as a feature for the detection of QRS-complexes, P- and T-waves. The performance of the algorithm is validated using original 12-lead ECG recordings from the standard CSE ECG database. Significant detection rate is achieved. The percentage of false positive and false negative detection is low. The method successfully detects all kind of morphologies of QRS-complexes, P- and T-waves. The onsets and offsets of the detected QRS-complexes, P- and T-waves are found to be within the tolerance limits given in CSE library.     

Flow regimes in a two phase reversed flow jet loop bioreactor

Reversed flow jet loop bioreactors (RFJLB) have been used extensively for 2 or 3 phase biochemical reactions. From visual observations and gas holdup data, 3 distinct flow regimes are identified in RFJLB, namely: (1) Bubble free regime (BFR), where bubbles are observed in the draft tube only; (2) Transition regime (TR), where bubbles are observed in both the draft tube and the annulus, but without circulation; and (3) Complete bubble circulation regime (CBCR), where bubbles circulate in both the draft tube and annulus. CBCR is the most desirable regime, since the reactor operation in this regime gives a higher gas holdup and mass transfer rate than in the other two regimes. In the present study, the hydrodynamic behavior of RFJLB was investigated under various operational and geometrical conditions, such as gas and liquid velocity and nozzle configuration. Factors affecting the critical liquid circulation velocity (CLCV) above which the CBCR is established were identified and evaluated quantitatively.     

A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets

Background  

Gene selection is an important step when building predictors of disease state based on gene expression data. Gene selection generally improves performance and identifies a relevant subset of genes. Many univariate and multivariate gene selection approaches have been proposed. Frequently the claim is made that genes are co-regulated (due to pathway dependencies) and that multivariate approaches are therefore per definition more desirable than univariate selection approaches. Based on the published performances of all these approaches a fair comparison of the available results can not be made. This mainly stems from two factors. First, the results are often biased, since the validation set is in one way or another involved in training the predictor, resulting in optimistically biased performance estimates. Second, the published results are often based on a small number of relatively simple datasets. Consequently no generally applicable conclusions can be drawn.