A biomimetic sensor for the detection of lead in water.

The monitoring of lead (II) ions (Pb(2+)) in water is essential for both human health and the environment. Herein, a simple yet innovative biosensor for Pb(2+) detection is presented. The sensor is developed by the self-assembly of gold nanoparticles (GNPs) core-satellite structure using naturally occurring tripeptide glutathione (GSH) as linker. The addition of Pb(2+) caused a red-to-blue color change and the localized surface plasmon resonance (LSPR) band was shifted to ca. 650nm. The limit of detection (LOD) is found to be 47.6nM (9.9ppb) by UV-vis spectroscopy with high selectivity against other heavy metals. This method offers a new strategy for heavy metal detection using functionalized GNPs.

Collagen type-I leads to in vivo matrix mineralization and secondary stabilization of Mg-Zr-Ca alloy implants

Biodegradable magnesium-zirconia-calcium (Mg-Zr-Ca) alloy implants were coated with Collagen type-I (Coll-I) and assessed for their rate and efficacy of bone mineralization and implant stabilization. The phases, microstructure and mechanical properties of these alloys were analyzed using X-ray diffraction (XRD), optical microscopy and compression test, respectively, and the corrosion behavior was established by their hydrogen production rate in simulated body fluid (SBF). Coll-I extracted from rat tail, and characterized using fourier transform infrared (FT-IR) spectroscopy, was used for dip-coating the Mg-based alloys. The coated alloys were implanted into the femur bones of male New Zealand white rabbits. In vivo bone formation around the implants was quantified by measuring the bone mineral content/density (BMC/BMD) using dual-energy X-ray absorptiometry (DXA). Osseointegration of the implant and new bone mineralization was visualized by histological and immunohistochemical analysis. Upon surface coating with Coll-I, these alloys demonstrated high surface energy showing enhanced performance as an implant material that is suitable for rapid and efficient new bone tissue induction with optimal mineral content and cellular properties. The results demonstrate that Coll-I coated Mg-Zr-Ca alloys have a tendency to form superior trabecular bone structure with better osteoinduction around the implants and higher implant secondary stabilization, through the phenomenon of contact osteogenesis, compared to the control and uncoated ones in shorter periods of implantation. Hence, Coll-I surface coating of Mg-Zr-Ca alloys is a promising method for expediting new bone formation in vivo and enhancing osseointegration in load bearing implant applications.

Sulfur-impregnated, sandwich-type, hybrid carbon nanosheets with hierarchical porous structure for high-performance lithium-sulfur batteries

Sandwich-type hybrid carbon nanosheets (SCNMM) consisting of graphene and micro/mesoporous carbon layer are fabricated via a double template method using graphene oxide as the shape-directing agent and SiO2 nanoparticles as the mesoporous guide. The polypyrrole synthesized in situ on the graphene oxide sheets is used as a carbon precursor. The micro/mesoporous strcutures of the SCNMM are created by a carbonization process followed by HF solution etching and KOH treatment. Sulfur is impregnated into the hybrid carbon nanosheets to generate S@SCNMM composites for the cathode materials in Li-S secondary batteries. The microstructures and electrochemical performance of the as-prepared samples are investigated in detail. The hybrid carbon nanosheets, which have a thickness of about 10-25 nm, high surface area of 1588 m2 g-1, and broad pore size distribution of 0.8-6.0 nm, are highly interconnected to form a 3D hierarchical structure. The S@SCNMM sample with the sulfur content of 74 wt% exhibits excellent electrochemical performance, including large reversible capacity, good cycling stability and coulombic efficiency, and good rate capability, which is believed to be due to the structure of hybrid carbon materials with hierarchical porous structure, which have large specific surface area and pore volume.

Habitat classification of temperate marine macroalgal communities using bathymetric LiDAR

Here, we evaluated the potential of using bathymetric Light Detection and Ranging (LiDAR) to characterise shallow water (<30 m) benthic habitats of high energy subtidal coastal environments. Habitat classification, quantifying benthic substrata and macroalgal communities, was achieved in this study with the application of LiDAR and underwater video groundtruth data using automated classification techniques. Bathymetry and reflectance datasets were used to produce secondary terrain derivative surfaces (e.g., rugosity, aspect) that were assumed to influence benthic patterns observed. An automated decision tree classification approach using the Quick Unbiased Efficient Statistical Tree (QUEST) was applied to produce substrata, biological and canopy structure habitat maps of the study area. Error assessment indicated that habitat maps produced were primarily accurate (>70%), with varying results for the classification of individual habitat classes; for instance, producer accuracy for mixed brown algae and sediment substrata, was 74% and 93%, respectively. LiDAR was also successful for differentiating canopy structure of macroalgae communities (i.e., canopy structure classification), such as canopy forming kelp versus erect fine branching algae. In conclusion, habitat characterisation using bathymetric LiDAR provides a unique potential to collect baseline information about biological assemblages and, hence, potential reef connectivity over large areas beyond the range of direct observation. This research contributes a new perspective for assessing the structure of subtidal coastal ecosystems, providing a novel tool for the research and management of such highly dynamic marine environments. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

Chemiluminescence detection of MDMA in street drug samples using tris (2,2'-bipyridine) ruthenium (III)

Tris(2,2'-bipyridine)ruthenium(II) chemiluminescence was investigated for the detection of 3,4-methylenedioxymethamphetamine (MDMA) and several related compounds in street drug samples. Optimization using flow injection analysis showed that the selectivity of the reagent can be targeted towards the detection of secondary amines by altering the pH of the reaction environment. The greater selectivity of this mode of detection, compared to UV-absorbance, reduces the probability of false positive results from interfering compounds. The detection limit for MDMA under these conditions was 0.48 μM. A HPLC method incorporating post-column tris(2,2'-bipyridine)ruthenium(II) chemiluminescence detection was applied to the determination of MDMA in five street drug samples. The results obtained were in good agreement with quantification performed using traditional UV-absorbance detection, which demonstrates the viability of this method for confirmatory analysis of drug samples. This is the first report of tris(2,2'-bipyridine)ruthenium(II) chemiluminescence for the detection of MDMA and related amphetamine derivatives.

Mountain barriers and river conduits: phylogeographical structure in a large, mobile lizard (Varanidae: Varanus varius) from eastern Australia

Aim: Across eastern Australia, mountain ranges (the Great Dividing Range) and river catchments (the Murray-Darling Basin) are likely to have shaped the phylogeographical structure of many species. We address how such processes have influenced the phylogeography of the lace monitor, Varanus varius, a large mobile lizard. Location: Eastern and south-eastern Australia. Methods: Phylogeographical hypotheses were tested using up to 90 museum and field-collected samples from across the entire species' range; a 671-bp region of the mtDNA gene ND4 was sequenced and all individuals were genotyped (eight microsatellite loci). Results: Maximum-likelihood analysis of sequence data revealed three geographically separate clades, with divergences estimated to have occurred during the Pleistocene. The south-eastern clade showed an expansion pattern from northern refugia and dispersal appears to have occurred along the Murray-Darling river system. Microsatellite analyses support mtDNA clades but indicate secondary contact in the Hunter Valley, New South Wales. Main conclusions: Our results indicate that phylogeographical structure and contemporary gene flow in Varanus varius is shaped by dispersal capacity, geographical barriers and the presence of ancient river corridors. Indeed, only the most significant geological (McPherson Range) and habitat barriers (Burdekin Gap) appear to limit gene flow in this species. The expansion of the clade on the western side of the Great Dividing Range suggests that ancient riparian corridors have facilitated extensive gene flow. Our study highlights the importance of understanding a species' ecological dynamics when examining broad-scale evolutionary patterns.

Bayesian nonparametric approaches to abnormality detection in video surveillance

In data science, anomaly detection is the process of identifying the items, events or observations which do not conform to expected patterns in a dataset. As widely acknowledged in the computer vision community and security management, discovering suspicious events is the key issue for abnormal detection in video surveil-lance. The important steps in identifying such events include stream data segmentation and hidden patterns discovery. However, the crucial challenge in stream data segmenta-tion and hidden patterns discovery are the number of coherent segments in surveillance stream and the number of traffic patterns are unknown and hard to specify. Therefore, in this paper we revisit the abnormality detection problem through the lens of Bayesian nonparametric (BNP) and develop a novel usage of BNP methods for this problem. In particular, we employ the Infinite Hidden Markov Model and Bayesian Nonparamet-ric Factor Analysis for stream data segmentation and pattern discovery. In addition, we introduce an interactive system allowing users to inspect and browse suspicious events.

Quantitative secondary electron imaging for work function extraction at atomic level and layer identification of graphene

Two-dimensional (2D) materials usually have a layer-dependent work function, which require fast and accurate detection for the evaluation of their device performance. A detection technique with high throughput and high spatial resolution has not yet been explored. Using a scanning electron microscope, we have developed and implemented a quantitative analytical technique which allows effective extraction of the work function of graphene. This technique uses the secondary electron contrast and has nanometre-resolved layer information. The measurement of few-layer graphene flakes shows the variation of work function between graphene layers with a precision of less than 10 meV. It is expected that this technique will prove extremely useful for researchers in a broad range of fields due to its revolutionary throughput and accuracy.

An Electrochemical Sensor Based on Nanostructured Hollandite-type Manganese Oxide for Detection of Potassium Ions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Two-colour photocurrent detection technique for coherent control of a single InGaAs/GaAs quantum dot

We present a two-colour photocurrent detection method for coherent control of a single InGaAs/GaAs self-assembled quantum dot. A pulse shaping technique provides a high degree of control over picosecond optical pulses. Rabi rotations on the exciton to biexciton transition are presented, and fine structure beating is detected via time-resolved measurements. (c) 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Planning and Projects of Secondary Electric Power Distribution Systems

This paper proposes a methodology to achieve integrated planning and projects for secondary distribution circuits. The planning model is formulated as a mixed integer nonlinear programming problem (MINLP). In order to resolve this problem, a tabu search (TS) algorithm is used, with a neighborhood structure developed to explore the physical characteristics of specific geographies included in the planning and expansion of secondary networks, thus obtaining effective solutions as well as low operating costs and investments. The project stage of secondary circuits consists of calculating the mechanical efforts to determine the support structures of the primary and secondary distribution systems and determining the types of structures that should be used in the system according to topological and electrical parameters of the network and, therefore, accurately assessing the costs involved in the construction and/or reform of secondary systems. A constructive heuristic based on information of the electrical and topological conditions between the medium voltage and low voltage systems is used to connect the primary systems and secondary circuits. The results obtained from planning and design simulations of a real secondary system of electric energy distribution are presented.

Experimental damage detection grammian matrix

Structural Health Monitoring (SHM) has diverse potential applications, and many groups work in the development of tools and techniques for monitoring structural performance. These systems use arrays of sensors and can be integrated with remote or local computers. There are several different approaches that can be used to obtain information about the existence, location and extension of faults by non destructive tests. In this paper an experimental technique is proposed for damage location based on an observability grammian matrix. The dynamic properties of the structure are identified through experimental data using the eigensystem realization algorithm (ERA). Experimental tests were carried out in a structure through varying the mass of some elements. Output signals were obtained using accelerometers.

Structural damage detection by fuzzy clustering

The development of strategies for structural health monitoring (SHM) has become increasingly important because of the necessity of preventing undesirable damage. This paper describes an approach to this problem using vibration data. It involves a three-stage process: reduction of the time-series data using principle component analysis (PCA), the development of a data-based model using an auto-regressive moving average (ARMA) model using data from an undamaged structure, and the classification of whether or not the structure is damaged using a fuzzy clustering approach. The approach is applied to data from a benchmark structure from Los Alamos National Laboratory, USA. Two fuzzy clustering algorithms are compared: fuzzy c-means (FCM) and Gustafson-Kessel (GK) algorithms. It is shown that while both fuzzy clustering algorithms are effective, the GK algorithm marginally outperforms the FCM algorithm. (C) 2008 Elsevier Ltd. All rights reserved.

Damage Detection in Flexible Plate Using Lamb Waves

This paper presents an experimental technique for structural health monitoring (SHM) based on Lamb waves approach in an aluminum plate using piezoelectric material as actuators and sensors. Lamb waves are a form of elastic perturbation that remains guided between two parallel free surfaces, such as the upper and lower surfaces of a plate, beam or shelf. Lamb waves are formed when the actuator excites the surface of the structure with a pulse after receiving a signal. Two PZTs were placed in the plate surface and one of them was used to send a predefined wave through the structure. Thus, the other PZT (adjacent) becomes the sensor. Using this methodology, this paper presents one case of damage detection considering the aluminum plate in the free-free-free-free boundary condition. The damage was simulated by adding additional mass on the plate. It is proposed two damage detection indexes obtained from the experimental signal, involving the Fast Fourier Transform (FFT) and the power spectral density (PSD) that were computed using the output signal. The results show the viability of the presented methodology to damage detection in smart structures

Seasonal development of secondary xylem and phloem in Schizolobium parahyba (Vell.) Blake (Leguminosae : Caesalpinioideae)

The cambial activity and periodicity of secondary xylem and phloem formation have been less studied in tropical tree species than in temperate ones. This paper describes the relationship between seasonal cambial activity, xylem and phloem development, and phenology in Schizolobium parahyba, a fast growing semideciduous seasonal forest tree from southeastern Brazil. From 2002 to 2003, wood samples were collected periodically and phenology and climate were recorded monthly in the same period. S. parahyba forms annual growth increments in wood, delimited by narrow initial parenchyma bands. The reduction of the cambial activity to a minimum correlates to the dry season and leaf fall. The higher cambial activity correlates to the wet season and the presence of mature leaves. In phloem, a larger conductive region was observed in the wet season, when the trees were in full foliage. The secondary phloem did not exhibit any incremental zone marker; however, we found that the axial parenchyma tends to form irregular bands.