A terrestrial biotic ligand model. 1. Development and application to Cu and Ni toxicities to barley root elongation in soils

A Terrestrial Biotic Ligand Model (TBLM) was developed using noncalcareous soils from Europe based on Cu and Ni speciation and barley (Hordeum vulgare cv. Regina) root elongation bioassays. Free metal ion (M2+) activity was computed by the WHAM VI model using inputs of soil metal, soil organic matter, and alkali and alkaline earth metals concentrations, and pH in soil solution. The TBLM assumes that metal in soil and in the solution are in equilibrium. Metal ions react with the biotic ligand, the receptor site, and inhibit root elongation. Other ions, principally H+, Ca2+ and Mg2+, compete with M2+ and, therefore, affect its toxicity. Toxicity is correlated only to the fraction of the total biotic ligand sites occupied by M2+. Compared to other models using either the soil metal concentration or M2+ activity as the toxic dose, the TBLM provides a more consistent method to normalize and compare Cu and Ni toxicities to root elongation among different soils. The TBLM was able to predictthe EC50 soil Cu and Ni concentrations generally within a factor of 2 of the observed values, a level of precision similar to that for the aquatic Biotic Ligand Model, indicating its potential utility in metals risk assessment in soils.     

High-Resolution Elemental Bioimaging of Ca, Mn, Fe, Co, Cu, and Zn Employing LA-ICP-MS and Hydrogen Reaction Gas

Imaging of trace metal distribution in tissue sections by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) is typically performed using spatial resolutions of 30 μm(2) and above. Higher resolution imaging is desirable for many biological applications in order to approach the dimensions of a single cell. The limiting factor for increasing resolution is sensitivity, where signal-to-noise ratios are poor due to inherent background spectral interferences and reduced sample volume with decreasing laser beam diameter. Several prominent spectral interferences are present for a number of biologically relevant isotopes, including the (40)Ar(16)O(+) spectral interference on (56)Fe(+). We examined if H(2) as a reaction gas could improve the analytical performance of imaging experiments for a range of masses with spectral interferences. At low (<1 mL min(-1)) H(2) flow rates, greater spectral interference due to H(+) adducts was observed for (55)Mn, (57)Fe, and (59)Co. At higher flow rates of up to 3 mL H(2) per minute, the spectral interferences were reduced leading to improvement in limits of analysis for masses with O- and N-based polyatomic interferences. Enhanced sensitivity with the reaction cell allowed construction of high resolution (6 μm(2)) imaging of (56)Fe in the mouse brain that approached the dimensions of single cells.     

Thermogravimetric analysis as a new method to determine the lignocellulosic composition of biomass

Biomass energy uses organic matter such as wood or plants - lignocellulosic biomass - for creating heat, generating electricity and producing green oil for cars. Modern biomass energy recycles organic leftovers from forestry and agriculture, like corn stovers, rice husks, wood waste and pressed sugar cane, or uses special, fast-growing “energy crops” like willow and switchgrass, as fuel. Biomass is composed of three major components: cellulose, hemicelluloses, and lignin. Their differences in chemical structures lead to different chemical reactivities, making the relative composition in cellulose, hemicelluloses and lignin in the biomass a crucial factor for process design. In this paper thermogravimetric analysis is investigated as a new method to obtain lignin, hemicellulose and ??-cellulose contents in biomass. It is shown that this alternative method lead to comparable results than common methods used for the determination of the ??-cellulose content, with an enhancement of the accuracy in the determination of the hemicellulose content. Unfortunately, this method cannot be adopted for the determination of the lignin amount.     

Use of Impedance Probe for Estimation of Porosity Changes in Saturated Granular Filters under Cyclic Loading: Calibration and Application

Gravimetric and volumetric sampling techniques are reliable for the measurement of porosity in fully saturated granular filters. However, both methods require a significant effort to gather and prepare samples, are time intensive to process, and do not capture real-time changes. Portable impedance probes serve as a valuable alternative to these destructive and laborious sampling methods. These probes measure the dielectric properties of the soil-water mixtures from which the porosity of filters may be inferred. This study demonstrates that generalized calibrations can result in large errors for porosity estimation when using diverse and small-scale filter types. By comparing with gravimetric and volumetric based porosity measurements for saturated granular filter porosity, impedance probes with filter-specific calibration offer the reliability and confidence owing to its reduced error in a quick, nondestructive fashion. This paper also presents the results of a laboratory investigation using an impedance probe to monitor real-time changes in the porosity of saturated granular filters subjected to cyclic train loading.     

Prediction of sand mass and organic matter distribution via in situ measured wet sediment bulk density profile

The objective of the study is to develop a spatial prediction model of sand mass and organic matter distribution in an urban stormwater holding pond using in situ measured wet sediment bulk density profile data to spatially distinguish the most likely contaminated sediment deposit areas. The wet bulk density profiles of deposited sediment at 25 locations in the Berembang (Malaysia) stormwater holding pond were measured using a single-probe nuclear density gauge. The sand and organic matter compositions of the surface sediment sample, 5 cm thickness from the bed surface, were determined. Discriminant analysis (DA) was conducted to generate two Fisher’s linear discriminant functions for the prediction of sand mass and organic matter composition areas, respectively. The linear discriminant functions generated better area classifications of surface organic matter composition compared to the sand mass distribution using wet sediment bulk density data measured at more than 15 cm depth levels.     

High‐Sensitivity Real‐Time Analysis of Nanoparticle Toxicity in Green Fluorescent Protein‐Expressing Zebrafish

Gold nanoparticles (AuNP) show great potential for diagnostic and therapeutic application in humans. A great number of studies have tested the cytotoxicity of AuNP using cell culture. There is, however, an urgent need to test AuNP in vertebrate animal models that interrogate biodistribution and complex biological traits like organ development, whole body metabolism, and cognitive function. The sheer number of different compounds precludes the use of small rodent model for initial screening. The extended fish embryo test (FET) is used here to bridge the gap between cell culture and small animal models. A study on the toxicity of ultrasmall AuNP in wild type and transgenic zebrafish is presented. FET faithfully reproduce all important findings of a previous study in HeLa cells and add new important information on teratogenicity and hepatotoxicity that could not be gained from studying cultured cells.     

A frontal Delaunay quad mesh generator using the L ∞ norm

In a recent work, a new indirect method to generate all‐quad meshes has been developed. It takes advantage of a well‐known algorithm of the graph theory, namely the Blossom algorithm, which computes in polynomial time the minimum cost perfect matching in a graph. In this paper, we describe a method that allows to build triangular meshes that are better suited for recombination into quadrangles. This is performed by using the infinity norm to compute distances in the meshing process. The alignment of the elements in the frontal Delaunay procedure is controlled by a cross field defined on the domain. Meshes constructed this way have their points aligned with the cross‐field directions, and their triangles are almost right everywhere. Then, recombination with the Blossom‐based approach yields quadrilateral meshes of excellent quality. Copyright © 2013 John Wiley & Sons, Ltd.     

A hierarchical approach for the synthesis of batch water network

This work addresses the problem of synthesising cost-effective batch water networks where a number of process sources along with fresh water are mixed, stored, and assigned to process sinks. In order to address the complexity of the problem, a three-stage hierarchical approach is proposed. In the first stage, global targets are identified by formulating and solving a linear transportation problem for minimum water usage, maximum water recycle, and minimum wastewater discharge. These targets are determined a priori and without commitment to the network configuration. Next, a network with minimum number of tanks is synthesised by solving a mixed-integer non-linear program. The bilinear constraints are relaxed to transform the program into a mixed-integer linear program that is globally solvable. The third stage is aimed at simplifying the network configuration by minimising the number of network inter-connections. Insights gained from the water pinch analysis are also incorporated into the approach to further reduce the water flows via the placement of water regeneration unit. A case study is solved to illustrate the effectiveness of the proposed procedure.     

Development of a neural-based forecasting tool to classify recreational water quality using fecal indicator organisms

Users of recreational waters may be exposed to elevated pathogen levels through various point/non-point sources. Typical daily notifications rely on microbial analysis of indicator organisms (e.g., Escherichia coli) that require 18, or more, hours to provide an adequate response. Modeling approaches, such as multivariate linear regression (MLR) and artificial neural networks (ANN), have been utilized to provide quick predictions of microbial concentrations for classification purposes, but generally suffer from high false negative rates. This study introduces the use of learning vector quantization (LVQ) - a direct classification approach - for comparison with MLR and ANN approaches and integrates input selection for model development with respect to primary and secondary water quality standards within the Charles River Basin (Massachusetts, USA) using meteorologic, hydrologic, and microbial explanatory variables. Integrating input selection into model development showed that discharge variables were the most important explanatory variables while antecedent rainfall and time since previous events were also important. With respect to classification, all three models adequately represented the non-violated samples (>90%). The MLR approach had the highest false negative rates associated with classifying violated samples (41-62% vs 13-43% (ANN) and <16% (LVQ)) when using five or more explanatory variables. The ANN performance was more similar to LVQ when a larger number of explanatory variables were utilized, but the ANN performance degraded toward MLR performance as explanatory variables were removed. Overall, the use of LVQ as a direct classifier provided the best overall classification ability with respect to violated/non-violated samples for both standards.     

建筑师未来的角色

在过去,建筑师可能只需负责建筑物的设计,但随着工程的规模愈来愈大,科技的创新以及社会对建筑要求的提升,建筑师要承担的工作和责任也越来越多.未来的建筑师要负责设计团队的管理、工程施工的监管、项目发展的策划、建筑与城市的协调、建材的创新和科研、工程造价和时间的掌握等多项工作,他们要能广又能专.预期未来会出现专科的建筑师,并期盼中国在建筑科技的改进中可以扮演重要角色.