Corneal confocal microscopy : a novel noninvasive means to diagnose neuropathy in patients with Fabry disease

ABSTRACT: Neuropathy is a cause of significant disability in patients with Fabry disease, yet its diagnosis is difficult. In this study we compared the novel noninvasive techniques of corneal confocal microscopy (CCM) to quantify small-fiber pathology, and non-contact corneal esthesiometry (NCCA) to quantify loss of corneal sensation, with established tests of neuropathy in patients with Fabry disease. Ten heterozygous females with Fabry disease not on enzyme replacement therapy (ERT), 6 heterozygous females, 6 hemizygous males on ERT, and 14 age-matched, healthy volunteers underwent detailed quantification of neuropathic symptoms, neurological deficits, neurophysiology, quantitative sensory testing (QST), NCCA, and CCM. All patients with Fabry disease had significant neuropathic symptoms and an elevated Mainz score. Peroneal nerve amplitude was reduced in all patients and vibration perception threshold was elevated in both male and female patients on ERT. Cold sensation (CS) threshold was significantly reduced in both male and female patients on ERT (P < 0.02), but warm sensation (WS)and heat-induced pain (HIP) were only significantly increased in males onERT (P<0.01). However, corneal sensation assessed withNCCAwas significantly reduced in female (P < 0.02) and male (P < 0.04) patients on ERT compared with control subjects. According to CCM, corneal nerve fiber and branch density was significantly reduced in female (P < 0.03) and male (P < 0.02) patients on ERT compared with control subjects. Furthermore, the severity of neuropathic symptoms and the neurological component of the Mainz Severity Score Index correlated significantly with QSTand CCM. This study shows that CCM and NCCA provide a novel means to detect early nerve fiber damage and dysfunction, respectively, in patients with Fabry disease.

Structural health monitoring of bridges using acoustic emission technology and signal processing techniques

Structural health monitoring (SHM) is the term applied to the procedure of monitoring a structure’s performance, assessing its condition and carrying out appropriate retrofitting so that it performs reliably, safely and efficiently. Bridges form an important part of a nation’s infrastructure. They deteriorate due to age and changing load patterns and hence early detection of damage helps in prolonging the lives and preventing catastrophic failures. Monitoring of bridges has been traditionally done by means of visual inspection. With recent developments in sensor technology and availability of advanced computing resources, newer techniques have emerged for SHM. Acoustic emission (AE) is one such technology that is attracting attention of engineers and researchers all around the world. This paper discusses the use of AE technology in health monitoring of bridge structures, with a special focus on analysis of recorded data. AE waves are stress waves generated by mechanical deformation of material and can be recorded by means of sensors attached to the surface of the structure. Analysis of the AE signals provides vital information regarding the nature of the source of emission. Signal processing of the AE waveform data can be carried out in several ways and is predominantly based on time and frequency domains. Short time Fourier transform and wavelet analysis have proved to be superior alternatives to traditional frequency based analysis in extracting information from recorded waveform. Some of the preliminary results of the application of these analysis tools in signal processing of recorded AE data will be presented in this paper.

Integrated Diagnosis and Prognosis Model for High Pressure LNG Pump

In condition-based maintenance (CBM), effective diagnostics and prognostics are essential tools for maintenance engineers to identify imminent fault and to predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedules production if necessary. This paper presents a technique for accurate assessment of the remnant life of machines based on historical failure knowledge embedded in the closed loop diagnostic and prognostic system. The technique uses the Support Vector Machine (SVM) classifier for both fault diagnosis and evaluation of health stages of machine degradation. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for multi-class fault diagnosis. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

Raman spectroscopic study of the antimonate mineral brandholzite Mg[Sb(OH)12].6H2O

Raman spectra of brandholzite Mg[Sb(OH)6].6H2O were studied, complemented with infrared spectra, and related to the structure of the mineral. An intense Raman sharp band at 618 cm-1 is attributed to the SbO symmetric stretching mode. The low intensity band at 730 cm-1 is ascribed to the SbO antisymmetric stretching vibration. Low intensity Raman bands were found at 503, 526 and 578 cm-1. Corresponding infrared bands were observed at 527, 600, 637, 693, 741 and 788 cm-1. Four Raman bands observed at 1043, 1092, 1160 and 1189 cm-1 and eight infrared bands at 963, 1027, 1055, 1075, 1108, 1128, 1156 and 1196 cm-1 are assigned to δ SbOH deformation modes. A complex pattern resulting from the overlapping band of the water and hydroxyl units is observed. Raman bands are observed at 3240, 3383, 3466, 3483 and 3552 cm-1, infrared bands at 3248, 3434 and 3565 cm-1. The first two Raman bands and the first infrared band are assigned to water stretching vibrations. The two higher wavenumber Raman bands observed at 3466 and 3552 cm-1 and two infrared bands at 3434 and 3565 cm-1 are assigned to the stretching vibrations of the hydroxyl units. Observed Raman and infrared bands are connected with O-H…O hydrogen bonds and their lengths 2.72, 2.79, 2.86, 2.88 and 3.0 Å (Raman) and 2.73, 2.83 and 3.07 Å (infrared).

Raman spectroscopic study of the uranyl mineral pseudojohannite Cu6.5[(UO2)4O4(SO4)2]2(OH)5.25H2O

Raman spectra of pseudojohannite were studied and related to the structure of the mineral. Observed bands were assigned to the stretching and bending vibrations of (UO2)2+ and (SO4)2- units and of water molecules. The published formula of pseudojohannite is Cu6.5(UO2)8\[O8](OH)5\[(SO4)4].25H2O; however Raman spectroscopy does not detect any hydroxyl units. Raman bands at 805 and 810 cm-1 are assigned to (UO2)2+ stretching modes. The Raman bands at 1017 and 1100 cm-1 are assigned to the (SO4)2- symmetric and antisymmetric stretching vibrations. The three Raman bands at 423, 465 and 496 cm-1 are assigned to the (SO4)2- ν2 bending modes. The bands at 210 and 279 cm-1 are assigned to the doubly degenerate ν2 bending vibration of the (UO2)2+ units. U-O bond lengths in uranyl and O-H…O hydrogen bond lengths were calculated from the Raman and infrared spectra.

Dynamics deflection analysis of nanoelectromechanical switches based on carbon nanotubes

This paper aims to develop an effective numerical simulation technique for the dynamic deflection analysis of nanotubes-based nanoswitches. The nanoswitch is simplified to a continuum structure, and some key material parameters are extracted from typical molecular dynamics (MD). An advanced local meshless formulation is applied to obtain the discretized dynamic equations for the numerical solution. The developed numerical technique is firstly validated by the static deflection analyses of nanoswitches, and then, the fundamental dynamic properties of nanoswitches are analyzed. A parametric comparison with the results in the literature and from experiments shows that the developed modelling approach is accurate, efficient and effective.

Condition-based prognosis of machine health

Modern machines are complex and often required to operate long hours to achieve production targets. The ability to detect symptoms of failure, hence, forecasting the remaining useful life of the machine is vital to prevent catastrophic failures. This is essential to reducing maintenance cost, operation downtime and safety hazard. Recent advances in condition monitoring technologies have given rise to a number of prognosis models that attempt to forecast machinery health based on either condition data or reliability data. In practice, failure condition trending data are seldom kept by industries and data that ended with a suspension are sometimes treated as failure data. This paper presents a novel approach of incorporating historical failure data and suspended condition trending data in the prognostic model. The proposed model consists of a FFNN whose training targets are asset survival probabilities estimated using a variation of Kaplan-Meier estimator and degradation-based failure PDF estimator. The output survival probabilities collectively form an estimated survival curve. The viability of the model was tested using a set of industry vibration data.

The structure of selected magnesium carbonate minerals : a near infrared and mid-infrared spectroscopic study

The approach to remove green house gases by pumping liquid CO2 several kilometres below the ground implies that many carbonate containing minerals will be formed. Among these minerals the formation of dypingite and artinite are possible; thus necessitating a study of such minerals. Two carbonate bearing minerals dypingite and artinite with a hydrotalcite related formulae have been characterised by a combination of infrared and near-infrared spectroscopy. The infrared spectra of both minerals are characterised by OH and water stretching vibrations. Both the first and second fundamental overtones of these bands are observed in the NIR spectra in the 7030 to 7235 cm-1 and 10490 to 10570 cm-1. Intense (CO3)2- symmetric and antisymmetric stretching vibrations confirm the distortion of the carbonate anion. The position of the water bending vibration indicates water is strongly hydrogen bonded to the carbonate anion in the mineral structure. Split NIR bands at around 8675 and 11100 cm-1 indicates that some replacement of magnesium ions by ferrous ions in the mineral structure has occurred.