Coupling between elytra of some beetles: Mechanism, forces and effect of surface texture

Lightweight materials, structures and coupling mechanisms are very important for realizing advanced flight vehicles. Here, we obtained the geometric structures and morphologies of the elytra of beetles and ascertained its coupling zone by using the histological section technique and SEM. We set up a three-dimensional motion observing system to monitor the opening and closing behaviour of elytra in beetles and to determine the motion mechanism. We constructed a force measuring system to measure the coupling forces between elytra. The results show that elytra open and close by rotating about a single axle, where the coupling forces may be as high as 160 times its own bodyweight, the elytra coupling with the tenon and mortise mechanism, surface texture and opening angle between elytra heavily influence the coupling forces. These results may provide insights into the design mechanism and structure for future vehicles of flight.

Model structure and uncertainty for stochastic non-point source modelling applications

The uncertainty associated with a rainfall-runoff and non-point source loading (NPS) model can be attributed to both the parameterization and model structure. An interesting implication of the areal nature of NPS models is the direct relationship between model structure (i.e. sub-watershed size) and sample size for the parameterization of spatial data. The approach of this research is to find structural limitations in scale for the use of the conceptual NPS model, then examine the scales at which suitable stochastic depictions of key parameter sets can be generated. The overlapping regions are optimal (and possibly the only suitable regions) for conducting meaningful stochastic analysis with a given NPS model. Previous work has sought to find optimal scales for deterministic analysis (where, in fact, calibration can be adjusted to compensate for sub-optimal scale selection); however, analysis of stochastic suitability and uncertainty associated with both the conceptual model and the parameter set, as presented here, is novel; as is the strategy of delineating a watershed based on the uncertainty distribution. The results of this paper demonstrate a narrow range of acceptable model structure for stochastic analysis in the chosen NPS model. In the case examined, the uncertainties associated with parameterization and parameter sensitivity are shown to be outweighed in significance by those resulting from structural and conceptual decisions. © 2011 Copyright IAHS Press.

Interfacial recognition of human prostate-specific antigen by immobilized monoclonal antibody: effects of solution conditions and surface chemistry.

The specific recognition between monoclonal antibody (anti-human prostate-specific antigen, anti-hPSA) and its antigen (human prostate-specific antigen, hPSA) has promising applications in prostate cancer diagnostics and other biosensor applications. However, because of steric constraints associated with interfacial packing and molecular orientations, the binding efficiency is often very low. In this study, spectroscopic ellipsometry and neutron reflection have been used to investigate how solution pH, salt concentration and surface chemistry affect antibody adsorption and subsequent antigen binding. The adsorbed amount of antibody was found to vary with pH and the maximum adsorption occurred between pH 5 and 6, close to the isoelectric point of the antibody. By contrast, the highest antigen binding efficiency occurred close to the neutral pH. Increasing the ionic strength reduced antibody adsorbed amount at the silica-water interface but had little effect on antigen binding. Further studies of antibody adsorption on hydrophobic C8 (octyltrimethoxysilane) surface and chemical attachment of antibody on (3-mercaptopropyl)trimethoxysilane/4-maleimidobutyric acid N-hydroxysuccinimide ester-modified surface have also been undertaken. It was found that on all surfaces studied, the antibody predominantly adopted the 'flat on' orientation, and antigen-binding capabilities were comparable. The results indicate that antibody immobilization via appropriate physical adsorption can replace elaborate interfacial molecular engineering involving complex covalent attachments.

Automated sparse 3D point cloud generation of infrastructure using its distinctive visual features

The commercial far-range (>10 m) spatial data collection methods for acquiring infrastructure’s geometric data are not completely automated because of the necessary manual pre- and/or post-processing work. The required amount of human intervention and, in some cases, the high equipment costs associated with these methods impede their adoption by the majority of infrastructure mapping activities. This paper presents an automated stereo vision-based method, as an alternative and inexpensive solution, to producing a sparse Euclidean 3D point cloud of an infrastructure scene utilizing two video streams captured by a set of two calibrated cameras. In this process SURF features are automatically detected and matched between each pair of stereo video frames. 3D coordinates of the matched feature points are then calculated via triangulation. The detected SURF features in two successive video frames are automatically matched and the RANSAC algorithm is used to discard mismatches. The quaternion motion estimation method is then used along with bundle adjustment optimization to register successive point clouds. The method was tested on a database of infrastructure stereo video streams. The validity and statistical significance of the results were evaluated by comparing the spatial distance of randomly selected feature points with their corresponding tape measurements.

Automated 3D Structure Inference of Civil Infrastructure Using a Stereo Camera Set

The commercial far-range (>10m) infrastructure spatial data collection methods are not completely automated. They need significant amount of manual post-processing work and in some cases, the equipment costs are significant. This paper presents a method that is the first step of a stereo videogrammetric framework and holds the promise to address these issues. Under this method, video streams are initially collected from a calibrated set of two video cameras. For each pair of simultaneous video frames, visual feature points are detected and their spatial coordinates are then computed. The result, in the form of a sparse 3D point cloud, is the basis for the next steps in the framework (i.e., camera motion estimation and dense 3D reconstruction). A set of data, collected from an ongoing infrastructure project, is used to show the merits of the method. Comparison with existing tools is also shown, to indicate the performance differences of the proposed method in the level of automation and the accuracy of results.

Recovering 3D Structure of Poorly Textured Infrastructure Scenes Using Point and Line Features

Most of the existing automated machine vision-based techniques for as-built documentation of civil infrastructure utilize only point features to recover the 3D structure of a scene. However it is often the case in man-made structures that not enough point features can be reliably detected (e.g. buildings and roofs); this can potentially lead to the failure of these techniques. To address the problem, this paper utilizes the prominence of straight lines in infrastructure scenes. It presents a hybrid approach that benefits from both point and line features. A calibrated stereo set of video cameras is used to collect data. Point and line features are then detected and matched across video frames. Finally, the 3D structure of the scene is recovered by finding 3D coordinates of the matched features. The proposed approach has been tested on realistic outdoor environments and preliminary results indicate its capability to deal with a variety of scenes.

The Gaussian mixture MCMC particle algorithm for dynamic cluster tracking

We present a novel filtering algorithm for tracking multiple clusters of coordinated objects. Based on a Markov chain Monte Carlo (MCMC) mechanism, the new algorithm propagates a discrete approximation of the underlying filtering density. A dynamic Gaussian mixture model is utilized for representing the time-varying clustering structure. This involves point process formulations of typical behavioral moves such as birth and death of clusters as well as merging and splitting. For handling complex, possibly large scale scenarios, the sampling efficiency of the basic MCMC scheme is enhanced via the use of a Metropolis within Gibbs particle refinement step. As the proposed methodology essentially involves random set representations, a new type of estimator, termed the probability hypothesis density surface (PHDS), is derived for computing point estimates. It is further proved that this estimator is optimal in the sense of the mean relative entropy. Finally, the algorithm's performance is assessed and demonstrated in both synthetic and realistic tracking scenarios. © 2012 Elsevier Ltd. All rights reserved.

A performance evaluation of volumetric 3D interest point detectors

This paper presents the first performance evaluation of interest points on scalar volumetric data. Such data encodes 3D shape, a fundamental property of objects. The use of another such property, texture (i.e. 2D surface colouration), or appearance, for object detection, recognition and registration has been well studied; 3D shape less so. However, the increasing prevalence of 3D shape acquisition techniques and the diminishing returns to be had from appearance alone have seen a surge in 3D shape-based methods. In this work, we investigate the performance of several state of the art interest points detectors in volumetric data, in terms of repeatability, number and nature of interest points. Such methods form the first step in many shape-based applications. Our detailed comparison, with both quantitative and qualitative measures on synthetic and real 3D data, both point-based and volumetric, aids readers in selecting a method suitable for their application. © 2012 Springer Science+Business Media, LLC.

Sound radiation from point-driven shell structures

A numerical study is presented showing the structural response and sound radiation from a range of thin shell structures excited by a point force: a baffled flat plate, a sphere, a family of spheroids and a family of closed circular cylinders. All the structures have the same material properties, thickness and total surface area so the asymptotic modal density is the same. Dramatic differences are shown in the total radiated sound power for the different shells. It was already known that the flat plate and the sphere behave very differently. These results show that the cylinders and, particularly, the spheroids show patterns that are not intermediate between the two but instead display new features: in certain frequency ranges the radiated sound power can be at least an order of magnitude greater than either the plate or the sphere. © 2013 Elsevier Ltd.

Coupling model uncertainty for coupled rainfall/runoff and surface water quality models in river problems

Coupled hydrology and water quality models are an important tool today, used in the understanding and management of surface water and watershed areas. Such problems are generally subject to substantial uncertainty in parameters, process understanding, and data. Component models, drawing on different data, concepts, and structures, are affected differently by each of these uncertain elements. This paper proposes a framework wherein the response of component models to their respective uncertain elements can be quantified and assessed, using a hydrological model and water quality model as two exemplars. The resulting assessments can be used to identify model coupling strategies that permit more appropriate use and calibration of individual models, and a better overall coupled model response. One key finding was that an approximate balance of water quality and hydrological model responses can be obtained using both the QUAL2E and Mike11 water quality models. The balance point, however, does not support a particularly narrow surface response (or stringent calibration criteria) with respect to the water quality calibration data, at least in the case examined here. Additionally, it is clear from the results presented that the structural source of uncertainty is at least as significant as parameter-based uncertainties in areal models. © 2012 John Wiley & Sons, Ltd.

Physical properties of a hybrid and a nanohybrid dental light-cured resin composite.

This work was aimed at the study of some physical properties of two current light-cured dental resin composites, Rok (hybrid) and Ice (nanohydrid). As filler they both contain strontium aluminosilicate particles, however, with different size distribution, 40 nm-2.5 mum for Rok and 10 nm-1 mum for Ice. The resin matrix of Rok consists of UDMA, that of Ice of UDMA, Bis-EMA and TEGDMA. Degree of conversion was determined by FT-IR analysis. The flexural strength and modulus were measured using a three-point bending set-up according to the ISO-4049 specification. Sorption, solubility and volumetric change were measured after storage of composites in water or ethanol/water (75 vol%) for 1 day, 7 or 30 days. Thermogravimetric analysis was performed in air and nitrogen atmosphere from 30 to 700 degrees C. Surface roughness and morphology of the composites was studied by atomic force microscopy (AFM). The degree of conversion was found to be 56.9% for Rok and 61.0% for Ice. The flexural strength of Rok does not significantly differ from that of Ice, while the flexural modulus of Rok is higher than that of Ice. The flexural strengths of Rok and Ice did not show any significant change after immersion in water or ethanol solution for 30 days. The flexural modulus of Rok and Ice did not show any significant change either after immersion in water for 30 days, while it decreased significantly, even after 1 day immersion, in ethanol solution. Ice sorbed a higher amount of water and ethanol solution than Rok and showed a higher volume increase. Thermogravimetric analysis showed that Rok contains about 80 wt% inorganic filler and Ice about 75 wt%.

Obtaining the shape of a moving object with a specular surface

This paper addresses the basic problem of recovering the 3D surface of an object that is observed in motion by a single camera and under a static but unknown lighting condition. We propose a method to establish pixelwise correspondence between input images by way of depth search by investigating optimal subsets of intensities rather than employing all the relevant pixel values. The thrust of our algorithm is that it is capable of dealing with specularities which appear on the top of shading variance that is caused due to object motion. This is in terms of both stages of finding sparse point correspondence and dense depth search. We also propose that a linearised image basis can be directly computed by the procudure of finding the correspondence. We illustrate the performance of the theoretical propositions using images of real objects. © 2009. The copyright of this document resides with its authors.

A Single-Fundamental-Mode Photonic Crystal Vertical Cavity Surface Emitting Laser

Single-fundamental-mode photonic crystal (PhC) vertical cavity surface emitting lasers (VCSEL) are produced and their single-fundamental-mode performances are investigated and demonstrated. A two-dimensional PhC with single-point-defect structure is fabricated using UV photolithography and inductive coupled plasma reactive ion etching on the surface of the VCSEL's top distributed Bragg-reflector. The PhC VCSEL maintains single-fundamental-mode operating with output power 1.7 mW and threshold current 2.5 mA. The full width half maximum of the lasing spectrum is less than 0.1 nm, the far field divergence angle is less than 10 degrees and the side mode suppression ratio is over 35 dB. The device characteristics are analyzed based on the effective index model of the photonic crystal fiber. The experimental results agree well with the theoretical expectation.

Enhanced mid-infrared transmission in heavily doped n-type semiconductor film based on surface plasmons

Transmission of electromagnetic wave in a heavily doped n-type GaAs film is studied theoretically. From the calculations, an extraordinary transmission of p-polarized waves through the film with subwavelength grooves on both surfaces at mid-infrared frequencies is found. This extraordinary transmission is attributed to the coupling of the surface-plasmon polariton modes and waveguide modes. By selecting a set of groove parameters, the transmission is optimized to a maximum. Furthermore, the transmission can be tuned by dopant concentrations. As the dopant concentration increases, the peak position shifts to higher frequency but the peak value decreases.

Information geometry theory of high-dimension space and application for speaker independent continuous digit speech recognition

In the light of descriptive geometry and notions in set theory, this paper re-defines the basic elements in space such as curve and surface and so on, presents some fundamental notions with respect to the point cover based on the High-dimension space (HDS) point covering theory, finally takes points from mapping part of speech signals to HDS, so as to analyze distribution information of these speech points in HDS, and various geometric covering objects for speech points and their relationship. Besides, this paper also proposes a new algorithm for speaker independent continuous digit speech recognition based on the HDS point dynamic searching theory without end-points detection and segmentation. First from the different digit syllables in real continuous digit speech, we establish the covering area in feature space for continuous speech. During recognition, we make use of the point covering dynamic searching theory in HDS to do recognition, and then get the satisfying recognized results. At last, compared to HMM (Hidden Markov models)-based method, from the development trend of the comparing results, as sample amount increasing, the difference of recognition rate between two methods will decrease slowly, while sample amount approaching to be very large, two recognition rates all close to 100% little by little. As seen from the results, the recognition rate of HDS point covering method is higher than that of in HMM (Hidden Markov models) based method, because, the point covering describes the morphological distribution for speech in HDS, whereas HMM-based method is only a probability distribution, whose accuracy is certainly inferior to point covering.