Electromechanical modeling and experimental analysis of a compression-based piezoelectric vibration energy harvester

Over the past few decades, wireless sensor networks have been widely used in the field of structure health monitoring of civil, mechanical, and aerospace systems. Currently, most wireless sensor networks are battery-powered and it is costly and unsustainable for maintenance because of the requirement for frequent battery replacements. As an attempt to address such issue, this article theoretically and experimentally studies a compression-based piezoelectric energy harvester using a multilayer stack configuration, which is suitable for civil infrastructure system applications where large compressive loads occur, such as heavily vehicular loading acting on pavements. In this article, we firstly present analytical and numerical modeling of the piezoelectric multilayer stack under axial compressive loading, which is based on the linear theory of piezoelectricity. A two-degree-of-freedom electromechanical model, considering both the mechanical and electrical aspects of the proposed harvester, was developed to characterize the harvested electrical power under the external electrical load. Exact closed-form expressions of the electromechanical models have been derived to analyze the mechanical and electrical properties of the proposed harvester. The theoretical analyses are validated through several experiments for a test prototype under harmonic excitations. The test results exhibit very good agreement with the analytical analyses and numerical simulations for a range of resistive loads and input excitation levels. © 2014 The Author(s)

Future intelligent civil structures: Challenges and opportunities

An intelligent civil structure offers ultimate protection to its structure, contents and occupants in terms of safety and functionality against undesired dynamic loadings and structural deficiency. In this paper, the concept of the future intelligent civil structure featuring self-adaptive, selfprognostic, self-sensing, self-powering and self-repairing abilities, is proposed. A decade research efforts from Centre for Built Infrastructure Research, University of Technology Sydney, towards the development and concept proof of such intelligent structure is reviewed

Quality of care in patients with diabetic kidney disease in Asia: The Joint Asia Diabetes Evaluation (JADE) Registry

Aims: Diabetic kidney disease independently predicts cardiovascular disease and premature death. We examined the burden of chronic kidney disease (CKD, defined as an estimated GFR < 60 ml/min/1.73 m2) and quality of care in a cross-sectional survey of adults (age ≥ 18 years) with Type 2 diabetes across Asia. Methods: The Joint Asia Diabetes Evaluation programme is a disease-management programme implemented using an electronic portal that systematically captures clinical characteristics of all patients enrolled. Between July 2007 and December 2012, data on 28 110 consecutively enrolled patients (China: 3415, Hong Kong: 15 196, India: 3714, Korea: 1651, Philippines: 3364, Vietnam: 692, Taiwan: 78) were analysed. Results: In this survey, 15.9% of patients had CKD, 25.0% had microalbuminuria and 12.5% had macroalbuminuria. Patients with CKD were less likely to achieve HbA1c < 53 mmol/mol (7.0%) (36.0% vs. 42.3%) and blood pressure < 130/80 mmHg (20.8% vs. 35.3%), and were more likely to have retinopathy (26.2% vs. 8.7%), sensory neuropathy (29.0% vs. 7.7%), cardiovascular disease (26.6% vs. 8.7%) and self-reported hypoglycaemia (18.9% vs. 8.2%). Despite high frequencies of albuminuria (74.8%) and dyslipidaemia (93.0%) among CKD patients, only 49.0% were using renin–angiotensin system inhibitors and 53.6% were on statins. On logistic regression, old age, male gender, tobacco use, long disease duration, high HbA1c, blood pressure and BMI, and low LDL cholesterol were independently associated with CKD (all P < 0.05). Conclusions: The poor control of risk factors, suboptimal use of organ-protective drugs and high frequencies of hypoglycaemia highlight major treatment gaps in patients with diabetic kidney disease in Asia.postprin

A Modular Deep Learning Framework for Scene Understanding in Augmented Reality Applications

Taking as input natural images and videos augmented reality (AR) applications aim to enhance the real world with superimposed digital contents enabling interaction between the user and the environment. One important step in this process is automatic scene analysis and understanding that should be performed both in real time and with a good level of object recognition accuracy. In this work an end-to-end framework based on the combination of a Super Resolution network with a detection and recognition deep network has been proposed to increase performance and lower processing time. This novel approach has been evaluated on two different datasets: the popular COCO dataset whose real images are used for benchmarking many different computer vision tasks, and a generated dataset with synthetic images recreating a variety of environmental, lighting and acquisition conditions. The evaluation analysis is focused on small objects, which are more challenging to be correctly detected and recognised. The results show that the Average Precision is higher for smaller and low resolution objects for the proposed end-to-end approach in most of the selected conditions

Optimum pHs for Cr(VI) co-removal with nucleated Cu(II) precipitation in continuous-flow fluidised metal strippers

A compact nucleated precipitation technology using two fluidised sand columns in series was developed to pretreat model metal-plating wastewater containing high concentrations of Cu(II) and Cr(VI). Since either Cu(II) precipitation or Cr(VI) co-removal with Cu(II) precipitation was found to be highly pH dependent in batch tests, the continuous-flow studies were conducted under different pHs. Experimental results show that high pH has no positive influence on either Cr(VI) or Cu(II) removal in the continuous-flow fluidised metal stripper technology. Operation at pH 6.5 in both columns can obtain significantly higher levels of both total Cr(VI) and total Cu(II) removal compared with work at pH 9.5 in both columns and work at pH 6.5 and 9.5 in the 1st and 2nd columns, respectivel

A vibration-based approach for the estimation of the loss of composite action in timber composite systems

This paper presents a novel approach for the determination of the loss of composite action for timber composite systems using only measurements from non-destructive vibration testing. Traditionally, the composite action of a system is evaluated from static load testing using deflection measurements. However, static load testing is expensive, time consuming and inappropriate for existing flooring systems. The method proposed in this paper is based on the Damage Index (DI) method, which uses changes in modal strain energies, to detect locations and severities of damage. In the proposed method, a new Loss of Composite Action Index (LCAI), which is derived from direct mode shape measurements obtained from dynamic testing, is introduced to evaluate the loss of composite action. The proposed method is tested and validated on numerical and experimental models of a timber composite beam structure, which consists of two timber components that are connected with different numbers of screws to simulate various degrees of partial composite states. The results obtained from the new method are very encouraging and show a clear trend of the proposed dynamic-based LCAI in indicating the loss of composite action in the investigated timber composite structure. © (2013) Trans Tech Publicutions, Switzerland

A multicentre demonstration project to evaluate the effectiveness and acceptability of the web-based Joint Asia Diabetes Evaluation (JADE) programme with or without nurse support in Chinese patients with Type 2 diabetes

postprin

Superconductivity of ultra-fine tungsten nanowires grown by focused-ion-beam direct-writing

The electrical properties of lateral ultra-fine tungsten nanowires, which were grown by focused-ion-beam-induced deposition with 1 pA ion-beam current, were investigated. Temperature-dependent electrical measurements show that the wires are conducting and have a superconducting transition with a transition temperature (T-c) about 5.1 K. Resistance vs. temperature measurements reveal that, with decreasing cross-sectional area, the wires display an increasingly broad superconducting transition. A residual resistive tail extending down to the low-temperature region is found only for the thinnest tungsten nanowire, which is 10 nm thick and 19 nm wide. The logarithm of the residual resistance of this wire appears as two linear sections as a function of temperature, one within 300 mK below T-c and the other extending down to the lowest measuring temperature of 4.26 K. Such features have previously been identified with phase slip processes. Our results are suggestive that the focused-ion-beam technique might be a potential approach to fabricate ultra-thin and ultra-narrow nanowires for the study of superconducting suppression in nanoscale materials and for maskless superconducting device fabrication. (C) 2011 Elsevier B.V. All rights reserved

A chronological framework for colluviation during the last 110 kyr in KwaZulu/Natal

Luminescence dating techniques have been applied to colluvial sediments of the Masotcheni Formation. The ages obtained suggest that colluvial deposition occurred during late Oxygen Isotope Stage 5, after the peak of the Last Interglacial (Sub-stage 5e). Further colluvial deposition seems to have commenced early in Stage 3, following a period of donga erosion. A soil was then formed during Stage 3 in the top of this deposit at two of the sites, and this was covered by more colluvial deposits before Stage 3 ended. Evidence for late Holocene colluviation is also presented. -from Authorspublished_or_final_versio