Changes in Fish Communities in the Upper Patuxent River from 1966 to 1977

Ten year comparison of fish survey's with respect to diversity evenness and composition of fish communities. The upper Patuxent River was divided into Piedmont Plateau and Coastal Plain regions, not only for geographical purposes, but also because of the clustering of sewage treatment plants in the Coastal Plain region. In the Piedmont Plateau region, the fish species diversity changed very little from 1966 to 1977 ( Little Patuxent -- 2.82 to 2.66; Middle Patuxent -- 2.86 to 2.83; and main stem -- 2.46 to 2.63), except in a section of Little Patuxent River at and below the City of Columbia where the species diversity index showed a significant reduction from 2.97 to 1.99, and in a section of the main stem Patuxent River immediately downstream from the Brighton Dam of the Triadelphia Reservoir where the index increased significantly from 1.66 to 3.20. In the Coastal Plain region, a significant reduction in the fish species diversity index occurred between 1966 and 1977 below the two sewage treatment plant outfalls : Savage -- 2.69 to 0 and Patuxent-Crofton -- 3.06 to 1.33. Also, the substantial reduction in the species diversity index which had already occurred in 1966 below the six other plant: outfalls of Fort Meade No. I, Fort Meade No. 2, Maryland House of Correction, Maryland City , Parkway and Bowie, remained depressed in 1977. On the other hand, below the Horsepen Sewage Treatment Plant (a tertiary plant practicing dechlorination) the species diversity index increased from 1.91 to 2.8. (PDF contains 48 pages

Oscillations of Second-Order Neutral Impulsive Differential Equations

Necessary and sufficient conditions are established for oscillation of second-order neutral impulsive differential equation [y(t)+py(t-τ)]′′+qy(t-σ)=0, t≠tk, Δ(y′(tk)+py′(tk-τ))+q1y(tk-σ)=0, where the coefficients q,q1>0; p<0, τ,σ<0, and Δy(i)(tk)=y(i)(tk+)-y(i)(tk-), i=0,1

On the Fractional Difference Equations of Order (

This paper presents a kind of new definition of fractional difference, fractional summation, and fractional difference equations and gives methods for explicitly solving fractional difference equations of order (2,q)

High-performance blob-based iterative three-dimensional reconstruction in electron tomography using multi-GPUs

<p>Abstract</p> <p>Background</p> <p>Three-dimensional (3D) reconstruction in electron tomography (ET) has emerged as a leading technique to elucidate the molecular structures of complex biological specimens. Blob-based iterative methods are advantageous reconstruction methods for 3D reconstruction in ET, but demand huge computational costs. Multiple graphic processing units (multi-GPUs) offer an affordable platform to meet these demands. However, a synchronous communication scheme between multi-GPUs leads to idle GPU time, and a weighted matrix involved in iterative methods cannot be loaded into GPUs especially for large images due to the limited available memory of GPUs.</p> <p>Results</p> <p>In this paper we propose a multilevel parallel strategy combined with an asynchronous communication scheme and a blob-ELLR data structure to efficiently perform blob-based iterative reconstructions on multi-GPUs. The asynchronous communication scheme is used to minimize the idle GPU time so as to asynchronously overlap communications with computations. The blob-ELLR data structure only needs nearly 1/16 of the storage space in comparison with ELLPACK-R (ELLR) data structure and yields significant acceleration.</p> <p>Conclusions</p> <p>Experimental results indicate that the multilevel parallel scheme combined with the asynchronous communication scheme and the blob-ELLR data structure allows efficient implementations of 3D reconstruction in ET on multi-GPUs.</p

Necessary and sufficient conditions for oscillation of the solutions of even order differential equations

In this paper, we establish several necessary and sufficient conditions for oscillation of the solutions of the following even order differential equationx^{(n)}(t) + q(t)x^\gamma (t) = 0, \quad \mbox{$n$ is even},where $q(t) \in C([t_0 ,\infty ),{\mathbb R}^ + )$ and $\gamma$ is the quotient of odd positive integers

Hotspot Analysis of Spatial Environmental Pollutants Using Kernel Density Estimation and Geostatistical Techniques

Concentrations of four heavy metals (Cr, Cu, Ni, and Zn) were measured at 1,082 sampling sites in Changhua county of central Taiwan. A hazard zone is defined in the study as a place where the content of each heavy metal exceeds the corresponding control standard. This study examines the use of spatial analysis for identifying multiple soil pollution hotspots in the study area. In a preliminary investigation, kernel density estimation (KDE) was a technique used for hotspot analysis of soil pollution from a set of observed occurrences of hazards. In addition, the study estimates the hazardous probability of each heavy metal using geostatistical techniques such as the sequential indicator simulation (SIS) and indicator kriging (IK). Results show that there are multiple hotspots for these four heavy metals and they are strongly correlated to the locations of industrial plants and irrigation systems in the study area. Moreover, the pollution hotspots detected using the KDE are the almost same to those estimated using IK or SIS. Soil pollution hotspots and polluted sampling densities are clearly defined using the KDE approach based on contaminated point data. Furthermore, the risk of hazards is explored by these techniques such as KDE and geostatistical approaches and the hotspot areas are captured without requiring exhaustive sampling anywhere

Differential Diagnosis of Solitary Pulmonary Inflammatory Lesions and Peripheral Lung Cancers with Contrast-enhanced Computed Tomography

OBJECTIVES: To clarify differences between solitary pulmonary inflammatory lesions and peripheral lung cancers with contrast-enhanced computed tomography. METHODS: In total, 64 and 132 patients with solitary pulmonary inflammatory masses/nodules and peripheral lung cancers, respectively, were enrolled in this study. Their computed tomographic findings were summarized and compared retrospectively. RESULTS: Compared with the peripheral lung cancers, the inflammatory lesions were located closer to the pleura (

Increasing fMRI Sampling Rate Improves Granger Causality Estimates

Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show that such estimates are significantly improved when the temporal sampling rate of functional magnetic resonance imaging (fMRI) is increased 20-fold. Specifically, healthy volunteers performed a simple visuomotor task during blood oxygenation level dependent (BOLD) contrast based whole-head inverse imaging (InI). Granger causality analysis based on raw InI BOLD data sampled at 100-ms resolution detected the expected causal relations, whereas when the data were downsampled to the temporal resolution of 2 s typically used in echo-planar fMRI, the causality could not be detected. An additional control analysis, in which we SINC interpolated additional data points to the downsampled time series at 0.1-s intervals, confirmed that the improvements achieved with the real InI data were not explainable by the increased time-series length alone. We therefore conclude that the high-temporal resolution of InI improves the Granger causality connectivity analysis of the human brain

Fabricating core-shell WC@C/Pt structures and its enhanced performance for methanol electrooxidation

© 2017 Chinese Physical Society. The spray-dried spheres within a W/Pt multi-separation can be used to prepare discrete core-shell WC@C/Pt catalysts through a typical carburization production mechanism at 800 °C. In contrast with previous studies of the WC/Pt synthesis, the reaction observed here proceeds through an indirect annealing mechanism at 600 °C wherein species diffuse, thereby resulting in core-shell structure, and Pt nanoparticles were successfully dispersed in size/shape and randomly scattered across the in situ produced C spheres. Through direct carburization or at higher initial hydrochloroplatinic acid concentrations, however, complete reaction with core-shell spheres was not observed. Indirect carburization reduces the strain felt by the bonds featuring the larger WC particles and allows the motion of carbon around WC and Pt nanoparticles to be reserved, influencing the electrocatalytic performance and stability toward methanol oxidation

UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)