An optimized analytical method for the simultaneous detection of iodoform, iodoacetic acid, and other trihalomethanes and haloacetic acids in drinking water

An optimized method is presented using liquid-liquid extraction and derivatization for the extraction of iodoacetic acid (IAA) and other haloacetic acids (HAA9) and direct extraction of iodoform (IF) and other trihalomethanes (THM4) from drinking water, followed by detection by gas chromatography with electron capture detection (GC-ECD). A Doehlert experimental design was performed to determine the optimum conditions for the five most significant factors in the derivatization step: namely, the volume and concentration of acidic methanol (optimized values  = 15%, 1 mL), the volume and concentration of Na2SO4 solution (129 g/L, 8.5 mL), and the volume of saturated NaHCO3 solution (1 mL). Also, derivatization time and temperature were optimized by a two-variable Doehlert design, resulting in the following optimized parameters: an extraction time of 11 minutes for IF and THM4 and 14 minutes for IAA and HAA9; mass of anhydrous Na2SO4 of 4 g for IF and THM4 and 16 g for IAA and HAA9; derivatization time of 160 min and temperature at 40°C. Under optimal conditions, the optimized procedure achieves excellent linearity (R2 ranges 0.9990–0.9998), low detection limits (0.0008–0.2 µg/L), low quantification limits (0.008–0.4 µg/L), and good recovery (86.6%–106.3%). Intra- and inter-day precision were less than 8.9% and 8.8%, respectively. The method was validated by applying it to the analysis of raw, flocculated, settled, and finished waters collected from a water treatment plant in China

Impacts of forest changes on hydrology: a case study of large watersheds in the upper reaches of Minjiang River watershed in China

Quantifying the effects of forest changes on hydrology in large watersheds is important for designing forest or land management and adaptation strategies for watershed ecosystem sustainability. Minjiang River watershed, located in the upper reach of the Yangtze River basin, plays a strategic role in the environmental protection and economic and social well-being for both the watershed and the entire Yangtze River basin. The watershed lies in the transition zone from Sichuan Basin to Qinghai-Tibet Plateau with a size of 24 000 km<sup>2</sup>. Due to its strategic significance, severe historic deforestation and high sensitivity to climate change, the watershed has long been recognized as one of the highest priority watersheds in China for scientific research and resource management. The purpose of this review paper is to provide a state-of-the-art summary on what we have learned from several recently completed research programs (one of them known as "973 of the China National Major Fundamental Science" from 2002 to 2008). This summary paper focused on how land cover or forest change affected hydrology at both forest stand and watershed scales in this large watershed. Inclusion of two different spatial scales is useful, because the results from a small spatial scale (e.g. forest stand level) can help interpret the findings on a large spatial scale. Our review suggests that historic forest harvesting or land cover change has caused significant water yield increase due to reduction of forest canopy interception and evapotranspiration caused by removal of forest vegetation on both spatial scales. The impact magnitude caused by forest harvesting indicates that the hydrological effects of forest or land cover changes can be as important as those caused by climate change, while the opposite impact directions suggest their offsetting effects on water yield in the Minjiang River watershed. In addition, different types of forests have different magnitudes of evapotranspiration (ET), with the lowest in old-growth natural coniferous forests (<i>Abies faxoniana</i> Rehd. et Wils.) and the highest in coniferous plantations (e.g. <i>Picea asperata</i> Mast.) among major forest types in the study watershed. This suggests that selection of different types of forests can have an important role in ET and consequently water yield. Our synthesis indicates that future reforestation and climate change would likely produce the hydrological effects in the same direction and thus place double the pressure on water resource as both key drivers may lead to water yield reduction. The findings can support designing management strategies for protection of watershed ecological functions in the context of future land cover and climate changes

Quantum state engineering with flux-biased Josephson phase qubits by Stark-chirped rapid adiabatic passages

In this paper, the scheme of quantum computing based on Stark chirped rapid adiabatic passage (SCRAP) technique [L. F. Wei et al., Phys. Rev. Lett. 100, 113601 (2008)] is extensively applied to implement the quantum-state manipulations in the flux-biased Josephson phase qubits. The broken-parity symmetries of bound states in flux-biased Josephson junctions are utilized to conveniently generate the desirable Stark-shifts. Then, assisted by various transition pulses universal quantum logic gates as well as arbitrary quantum-state preparations could be implemented. Compared with the usual PI-pulses operations widely used in the experiments, the adiabatic population passage proposed here is insensitive the details of the applied pulses and thus the desirable population transfers could be satisfyingly implemented. The experimental feasibility of the proposal is also discussed.Comment: 9 pages, 4 figure

Frequency response function-based explicit framework for dynamic identification in human-structure systems

This is the final version. Available on open access from Elsevier via the DOI in this recordData accessibility: The data are self-contained in the paper.The aim of this paper is to propose a novel theoretical framework for dynamic identification in a structure occupied by a single human. The framework enables the prediction of the dynamics of the human-structure system from the known properties of the individual system components, the identification of human body dynamics from the known dynamics of the empty structure and the human-structure system and the identification of the properties of the structure from the known dynamics of the human and the human-structure system. The novelty of the proposed framework is the provision of closed-form solutions in terms of frequency response functions obtained by curve fitting measured data. The advantages of the framework over existing methods are that there is neither need for nonlinear optimisation nor need for spatial/modal models of the empty structure and the human-structure system. In addition, the second-order perturbation method is employed to quantify the effect of uncertainties in human body dynamics on the dynamic identification of the empty structure and the human-structure system. The explicit formulation makes the method computationally efficient and straightforward to use. A series of numerical examples and experiments are provided to illustrate the working of the method.Engineering and Physical Sciences Research Council (EPSRC

Effect of carbon nanotube doping on critical current density of MgB2 superconductor

The effect of doping MgB2 with carbon nanotubes on transition temperature, lattice parameters, critical current density and flux pinning was studied for MgB2-xCx with x = 0, 0.05, 0.1, 0.2 and 0.3. The carbon substitution for B was found to enhance Jc in magnetic fields but depress Tc. The depression of Tc, which is caused by the carbon substitution for B, increases with increasing doping level, sintering temperature and duration. By controlling the extent of the substitution and addition of carbon nanotubes we can achieve the optimal improvement on critical current density and flux pinning in magnetic fields while maintaining the minimum reduction in Tc. Under these conditions, Jc was enhanced by two orders of magnitude at 8T and 5K and 7T and 10K. Jc was more than 10,000A/cm2 at 20K and 4T and 5K and 8.5T, respectively

A 3D spatiotemporal morphological database for urban green infrastructure and its applications

The morphology of urban green infrastructure (UGI) will affect the quality of urban environment and the way people perceive. The three-dimensional morphological features of UGI have been proven to be the key factors to effect urban ecological environment, which have rarely been incorporated into the UGI morphology in the previous researches. In this paper, a systematic approach to develop a 3D spatiotemporal morphological database for UGI is proposed. The database is built on a complete set of information describing the form of UGI in the plane, the vertical direction and the temporal changes. In addition, three categories of morphological parameters of UGI are calculated and integrated in the database. User operation and visualization and morphological parameter operation is achievable in the database. The database can be further integrated with simulation programs and analytical models so that it can be used in the design and research of various urban sustainable subjects. In a case study, we further create a complete 3D spatiotemporal morphological database of UGI for an urban district of 4km² in Nanjing, China

A review of data-driven building performance analysis and design on big on-site building performance data

Building performance design (BPD) is a crucial pathway to achieve high-performance buildings. Previous simulation-based BPD is being questioned due to the performance gaps between simulated and measured values. In recent years, accumulated on-site building performance data (OBPD) make it possible to analyze and design buildings with data-driven methods. This article makes a review of previous studies that conducted data-driven building performance analysis and design on a large amount of OBPD. The covered studies are summarized by the applied techniques, i.e., statistics, regression, classification, and clustering. The data used by these studies are compared and discussed emphasizing the data size and public availability. A comprehensive discussion is given about the achievements of existing studies, and challenges for boosting data-driven BPD from three aspects, i.e., developing data-driven models, the availability of building performance data, and stimulation of industrial practices. The review results indicate that data-driven methods were commonly applied to estimate energy consumptions, and explore energy trends, determinant features, and reference buildings. Identifying determinant features is one of the most successful applications. This study highlights the future research gaps for boosting data-driven building performance design

The multiple benefits of brands and features: Evaluating the position of breads on health, taste, and value

We outline a framework outlining how product positioning occurs in a multi-dimensional consideration of brand benefits, whilst accounting for how product features further shape product positioning. Respondents evaluated supermarket breads described by brands and a variety of features (e.g., flour, claims, price). A holistic evaluation was made with respect to health, taste, value and overall preference. A brand’s relative position on multiple benefits was derived via a discrete choice model, simultaneously accounting for the impact that product features have on these same dimensions. This allows a direct comparison of the drivers of positioning from a holistic, multi-attribute multi-brand perspective. The results show the strong value that brands have in driving positioning, but also the role of some features in furthering this. The research compliments other frameworks and methods in product positioning, and we outline its extension to benefit segmentation