What knowledge do ICU nurses have with regard to the effects of noise exposure in the Intensive Care Unit?

This small-scale study was undertaken to assess what knowledge nursing staff from a General Intensive Care Unit held with regard to noise exposure. To assess knowledge a self-administered multiple-choice questionnaire was used. Rigorous peer-review insured content validity. This study produced poor results in terms of the knowledge nurses held with regard to noise related issues in particular the psychophysiological effects and current legislation concerning its safe exposure. Non-parametric testing, using Kruskal–Wallis found no significant difference between nursing grades, however, descriptive analysis demonstrated that the staff nurse grade (D and E) performed better overall. Whilst the results of this study may seem self-evident in some respects, it is the problems of exposure to excessive noise levels for both patients and hospital personnel, which are clearly not understood. The effects noise exposure has on individuals for example decreased wound healing; sleep deprivation and cardiovascular stimulation must be of concern especially in terms of patient care but more so for nursing staff especially the effects noise levels can have on cognitive task performance.

A rule-based hybrid method for anomaly detection in online-social-network graphs

Detecting anomalies in the online social network is a significant task as it assists in revealing the useful and interesting information about the user behavior on the network. This paper proposes a rule-based hybrid method using graph theory, Fuzzy clustering and Fuzzy rules for modeling user relationships inherent in online-social-network and for identifying anomalies. Fuzzy C-Means clustering is used to cluster the data and Fuzzy inference engine is used to generate rules based on the cluster behavior. The proposed method is able to achieve improved accuracy for identifying anomalies in comparison to existing methods.

Characterising an ECG signal using statistical modelling : a feasibility study

For clinical use, in electrocardiogram (ECG) signal analysis it is important to detect not only the centre of the P wave, the QRS complex and the T wave, but also the time intervals, such as the ST segment. Much research focused entirely on qrs complex detection, via methods such as wavelet transforms, spline fitting and neural networks. However, drawbacks include the false classification of a severe noise spike as a QRS complex, possibly requiring manual editing, or the omission of information contained in other regions of the ECG signal. While some attempts were made to develop algorithms to detect additional signal characteristics, such as P and T waves, the reported success rates are subject to change from person-to-person and beat-to-beat. To address this variability we propose the use of Markov-chain Monte Carlo statistical modelling to extract the key features of an ECG signal and we report on a feasibility study to investigate the utility of the approach. The modelling approach is examined with reference to a realistic computer generated ECG signal, where details such as wave morphology and noise levels are variable.

Novelty-based visual obstacle detection in agriculture

This paper describes a novel obstacle detection system for autonomous robots in agricultural field environments that uses a novelty detector to inform stereo matching. Stereo vision alone erroneously detects obstacles in environments with ambiguous appearance and ground plane such as in broad-acre crop fields with harvested crop residue. The novelty detector estimates the probability density in image descriptor space and incorporates image-space positional understanding to identify potential regions for obstacle detection using dense stereo matching. The results demonstrate that the system is able to detect obstacles typical to a farm at day and night. This system was successfully used as the sole means of obstacle detection for an autonomous robot performing a long term two hour coverage task travelling 8.5 km.

Acoustic, electric and virtual noise : the cultural identity of the guitar

Guitar technology underwent significant changes in the 20th century in the move from acoustic to electric instruments. In the first part of the 21st century, the guitar continues to develop through its interaction with digital technologies. Such changes in guitar technology are usually grounded in what we might call the "cultural identity" of the instrument: that is, the various ways that the guitar is used to enact, influence and challenge sociocultural and musical discourses. Often, these different uses of the guitar can be seen to reflect a conflict between the changing concepts of "noise" and "musical sound."

Tracking-based moving object detection

We present a novel approach for multi-object detection in aerial videos based on tracking. The proposed method mainly involves three steps. Firstly, the spatial-temporal saliency is employed to detect moving objects. Secondly, the detected objects are tracked by mean shift in the subsequent frames. Finally, the saliency results are fused with the weight map generated by tracking to get refined detection results, and in turn the modified detection results are used to update the tracking models. The proposed algorithm is evaluated on VIVID aerial videos, and the results show that our approach can reliably detect moving objects even in challenging situations. Meanwhile, the proposed method can process videos in real time, without the effect of time delay.

Moving object detection in aerial video based on spatiotemporal saliency

In this paper, the problem of moving object detection in aerial video is addressed. While motion cues have been extensively exploited in the literature, how to use spatial information is still an open problem. To deal with this issue, we propose a novel hierarchical moving target detection method based on spatiotemporal saliency. Temporal saliency is used to get a coarse segmentation, and spatial saliency is extracted to obtain the object’s appearance details in candidate motion regions. Finally, by combining temporal and spatial saliency information, we can get refined detection results. Additionally, in order to give a full description of the object distribution, spatial saliency is detected in both pixel and region levels based on local contrast. Experiments conducted on the VIVID dataset show that the proposed method is efficient and accurate.

Health monitoring of short-and medium-spen bridges using an improved modal strain energy method

Increasing the importance and use of infrastructures such as bridges, demands more effective structural health monitoring (SHM) systems. SHM has well addressed the damage detection issues through several methods such as modal strain energy (MSE). Many of the available MSE methods either have been validated for limited type of structures such as beams or their performance is not satisfactory. Therefore, it requires a further improvement and validation of them for different types of structures. In this study, an MSE method was mathematically improved to precisely quantify the structural damage at an early stage of formation. Initially, the MSE equation was accurately formulated considering the damaged stiffness and then it was used for derivation of a more accurate sensitivity matrix. Verification of the improved method was done through two plane structures: a steel truss bridge and a concrete frame bridge models that demonstrate the framework of a short- and medium-span of bridge samples. Two damage scenarios including single- and multiple-damage were considered to occur in each structure. Then, for each structure, both intact and damaged, modal analysis was performed using STRAND7. Effects of up to 5 per cent noise were also comprised. The simulated mode shapes and natural frequencies derived were then imported to a MATLAB code. The results indicate that the improved method converges fast and performs well in agreement with numerical assumptions with few computational cycles. In presence of some noise level, it performs quite well too. The findings of this study can be numerically extended to 2D infrastructures particularly short- and medium-span bridges to detect the damage and quantify it more accurately. The method is capable of providing a proper SHM that facilitates timely maintenance of bridges to minimise the possible loss of lives and properties.

Detection and quantification of tear phospholipids and cholesterol in contact lens deposits : the effect of contact lens material and lens care solution

PURPOSE. To examine the deposition of tear phospholipids and cholesterol onto worn contact lenses and the effect of lens material and lens care solution. METHODS. Lipids were extracted from tears and worn contact lenses using 2:1 chloroform: Methanol and the extract washed with aqueous ammonium acetate, before analysis by electrospray ionization tandem mass spectrometry (ESI-MS/MS). RESULTS. Twenty-three molecular lipids from the sphingomyelin (SM) and phosphatidylcholine (PC) classes were detected in tears, with total concentrations of each class determined to be 5 ± 1 pmol/μL (~3.8 μg/mL) and 6 ± 1 pmol/μL (~ 4.6μg/mL), respectively. The profile of individual phospholipids in both of these classes was shown to be similar in contact lens deposits. Deposition of representative polar and nonpolar lipids were shown to be significantly higher on senofilcon A contact lenses, with ~59 ng/lens SM, 195 ng/lens PC, and 9.9 μg/lens cholesterol detected, whereas balafilcon A lens extracts contained ~19 ng/lens SM, 19 ng/lens PC, and 3.9 μg/lens cholesterol. Extracts from lenses disinfected and cleaned with two lens care solutions showed no significant differences in total PC and SM concentrations; however, a greater proportion of PC than SM was observed, compared with that in tears. CONCLUSIONS. Phospholipid deposits extracted from worn contact lenses show a molecular profile similar to that in tears. The concentration of representative polar and nonpolar lipids deposited onto contact lenses is significantly affected by lens composition. There is a differential efficacy in the removal of PC and SM with lens care solutions.

Direct detection of additives and degradation products from polymers by liquid extraction surface analysis employing chip-based nanospray mass spectrometry

RATIONALE: Polymer-based surface coatings in outdoor applications experience accelerated degradation due to exposure to solar radiation, oxygen and atmospheric pollutants. These deleterious agents cause undesirable changes to the aesthetic and mechanical properties of the polymer, reducing its lifetime. The use of antioxidants such as hindered amine light stabilisers (HALS) retards these degradative processes; however, mechanisms for HALS action and polymer degradation are poorly understood. METHODS: Detection of the HALS TINUVINW123 (bis(1-octyloxy-2,2,6,6-tetramethyl-4-piperidyl) sebacate) and the polymer degradation products directly from a polyester-based coil coating was achieved by liquid extraction surface analysis (LESA) coupled to a triple quadrupole QTRAPW 5500 mass spectrometer. The detection of TINUVINW123 and melamine was confirmed by the characteristic fragmentation pattern observed in LESA-MS/MS spectra that was identical to that reported for authentic samples. RESULTS: Analysis of an unstabilised coil coating by LESA-MS after exposure to 4 years of outdoor field testing revealed the presence of melamine (1,3,5-triazine-2,4,6-triamine) as a polymer degradation product at elevated levels. Changes to the physical appearance of the coil coating, including powder-like deposits on the coating's surface, were observed to coincide with melamine deposits and are indicative of the phenomenon known as polymer ' blooming'. CONCLUSIONS: For the first time, in situ detection of analytes from a thermoset polymer coating was accomplished without any sample preparation, providing advantages over traditional extraction-analysis approaches and some contemporary ambient MS methods. Detection of HALS and polymer degradation products such as melamine provides insight into the mechanisms by which degradation occurs and suggests LESA-MS is a powerful new tool for polymer analysis. Copyright (C) 2012 John Wiley & Sons, Ltd.

Residential balconies with road traffic noise : a combined source image and radiosity model

Several significant studies have been made in recent decades toward understanding road traffic noise and its effects on residential balconies. These previous studies have used a variety of techniques such as theoretical models, scale models and measurements on real balconies. The studies have considered either road traffic noise levels within the balcony space or inside an adjacent habitable room or both. Previous theoretical models have used, for example, simplified specular reflection calculations, boundary element methods (BEM), adaptations of CoRTN or the use of Sabine Theory. This paper presents an alternative theoretical model to predict the effects of road traffic noise spatially within the balcony space. The model includes a specular reflection component by calculating up to 10 orders of source images. To account for diffusion effects, a two compartment radiosity component is utilised. The first radiosity compartment is the urban street, represented as a street with building facades on either side. The second radiosity compartment is the balcony space. The model is designed to calculate the predicted road traffic noise levels within the balcony space and is capable of establishing the effect of changing street and balcony geometries. Screening attenuation algorithms are included to determine the effects of solid balcony parapets and balcony ceiling shields.

Direct and quantitative detection of bacteriophage by “hearing” surface detachment using a quartz crystal microbalance

We show that it is possible to detect specifically adsorbed bacteriophage directly by breaking the interactions between proteins displayed on the phage coat and ligands immobilized on the surface of a quartz crystal microbalance (QCM). This is achieved through increasing the amplitude of oscillation of the QCM surface and sensitively detecting the acoustic emission produced when the bacteriophage detaches from the surface. There is no interference from nonspecifically adsorbed phage. The detection is quantitative over at least 5 orders of magnitude and is sensitive enough to detect as few as 20 phage. The method has potential as a sensitive and low-cost method for virus detection.

Direct and quantitative detection of bacteriophage by "hearing" surface detachment using a quartz crystal microbalance

We show that it is possible to detect specifically adsorbed bacteriophage directly by breaking the interactions between proteins displayed on the phage coat and ligands immobilized on the surface of a quartz crystal microbalance (QCM). This is achieved through increasing the amplitude of oscillation of the QCM surface and sensitively detecting the acoustic emission produced when the bacteriophage detaches from the surface. There is no interference from nonspecifically adsorbed phage. The detection is quantitative over at least 5 orders of magnitude and is sensitive enough to detect as few as 20 phage. The method has potential as a sensitive and low-cost method for virus detection.