Microbe-Based Sensor for Long-Term Detection of Urine Glucose.

The development of a reusable and low-cost urine glucose sensor can benefit the screening and control of diabetes mellitus. This study focused on the feasibility of employing microbial fuel cells (MFC) as a selective glucose sensor for continuous monitoring of glucose levels in human urine. Using MFC technology, a novel cylinder sensor (CS) was developed. It had a quick response time (100 s), a large detection range (0.3-5 mM), and excellent accuracy. More importantly, the CS could last for up to 5 months. The selectivity of the CS was validated by both synthetic and actual diabetes-negative urine samples. It was found that the CS's selectivity could be significantly enhanced by adjusting the concentration of the culture's organic matter. The CS results were comparable to those of a commercial glucose meter (recovery ranged from 93.6% to 127.9%) when the diabetes-positive urine samples were tested. Due to the multiple advantages of high stability, low cost, and high sensitivity over urine test strips, the CS provides a novel and reliable approach for continuous monitoring of urine glucose, which will benefit diabetes assessment and control.

Laser Ultrasound Inspection Based on Wavelet Transform and Data Clustering for Defect Estimation in Metallic Samples.

Laser-generated ultrasound is a modern non-destructive testing technique. It has been investigated over recent years as an alternative to classical ultrasonic methods, mainly in industrial maintenance and quality control procedures. In this study, the detection and reconstruction of internal defects in a metallic sample is performed by means of a time-frequency analysis of ultrasonic waves generated by a laser-induced thermal mechanism. In the proposed methodology, we used wavelet transform due to its multi-resolution time frequency characteristics. In order to isolate and estimate the corresponding time of flight of eventual ultrasonic echoes related to internal defects, a density-based spatial clustering was applied to the resulting time frequency maps. Using the laser scan beam's position, the ultrasonic transducer's location and the echoes' arrival times were determined, the estimation of the defect's position was carried out afterwards. Finally, clustering algorithms were applied to the resulting geometric solutions from the set of the laser scan points which was proposed to obtain a two-dimensional projection of the defect outline over the scan plane. The study demonstrates that the proposed method of wavelet transform ultrasonic imaging can be effectively applied to detect and size internal defects without any reference information, which represents a valuable outcome for various applications in the industry.

Fully Noncontact Hybrid NDT for 3D Defect Reconstruction Using SAFT Algorithm and 2D Apodization Window.

Nondestructive testing of metallic objects that may contain embedded defects of different sizes is an important application in many industrial branches for quality control. Most of these techniques allow defect detection and its approximate localization, but few methods give enough information for its 3D reconstruction. Here we present a hybrid laser-transducer system that combines remote, laser-generated ultrasound excitation and noncontact ultrasonic transducer detection. This fully noncontact method allows access to scan areas on different object's faces and defect details from different angles/perspectives. This hybrid system can analyze the object's volume data and allows a 3D reconstruction image of the embedded defects. As a novelty for signal processing improvement, we use a 2D apodization window filtering technique, applied along with the synthetic aperture focusing algorithm, to remove the undesired effects due to side lobes and wide-angle reflections of propagating ultrasound waves, thus enhancing the resulting 3D image of the defect. Finally, we provide both qualitative and quantitative volumetric results that yield valuable information about defect location and size.

Signal injection as a fault detection technique.

Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies.

Defect reconstruction by non-destructive testing with laser induced ultrasonic detection.

This work envisages a detailed study of two-dimensional defect localization and reconstruction, using laser generated ultrasound and its application as a remotely controlled non-destructive testing method. As an alternative to full ultrasonic or full optical approaches, we propose a hybrid configuration where ultrasound is generated by impact of laser pulses, while the detection is done with conventional transducers. We implement this approach for defect reconstruction in metallic elements and show that it combines advantages of both photonic and ultrasonic devices, reducing the drawbacks of both methods. We combine our experimental results with a high-resolution signal processing procedure based on the synthetic aperture focusing technique for the benefit of the final two-dimensional visualization of the defects.

One Dimensional AuAg Nanostructures as Anodic Catalysts in the Ethylene Glycol Oxidation.

Direct alcohol fuel cells are highly promising as efficient power sources for various mobile and portable applications. However, for the further advancement of fuel cell technology it is necessary to develop new, cost-effective Pt-free electrocatalysts that could provide efficient alcohol oxidation and also resist cross-over poisoning. Here, we report new electrocatalytic materials for ethylene glycol oxidation, which are based on AuAg linear nanostructures. We demonstrate a low temperature tunable synthesis that enables the preparation of one dimensional (1D) AuAg nanostructures ranging from nanowires to a new nano-necklace-like structure. Using a two-step method, we showed that, by aging the initial reaction mixture at various temperatures, we produced ultrathin AuAg nanowires with a diameter of 9.2 ± 2 and 3.8 ± 1.6 nm, respectively. These nanowires exhibited a high catalytic performance for the electro-oxidation of ethylene glycol with remarkable poisoning resistance. These results highlight the benefit of 1D metal alloy-based nanocatalysts for fuel cell applications and are expected to make an important contribution to the further development of fuel cell technology.

Pt and RhPt dendritic nanowires and their potential application as anodic catalysts for fuel cells.

Fuel cells have a number of benefits over conventional combustion-based technologies and can be used in a range of important applications, including transportation, as well as stationary, portable and emergency backup power systems. One of the major challenges in this field, however lies in controlling catalyst design which is critical for developing efficient and cost-effective fuel cell technology. Herein, for the first time, we report a facile controlled synthesis of Pt and RhPt dendritic nanowires using ultrathin AuAg nanowires as sacrificial templates. These dendritic nanowires exhibit remarkable catalytic performance in the elecrochemical oxidation of methanol and formic acid. In particular, the RhPt dendritic nanostructures show very high resistance to catalyst poisoning in methanol oxidation. This research demonstrates the advantages of using bimetallic dendritic nanostructures and we believe that these materials and electrocatalytic studies are important for further advancement of fuel cell research and technology.