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Sensors, Volume 12, Issue 7 (July 2012) – 81 articles , Pages 8438-9950

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263 KiB  
Article
A Logistic Regression Model for Predicting Axillary Lymph Node Metastases in Early Breast Carcinoma Patients
by Fei Xie, Houpu Yang, Shu Wang, Bo Zhou, Fuzhong Tong, Deqi Yang and Jiaqing Zhang
Sensors 2012, 12(7), 9936-9950; https://doi.org/10.3390/s120709936 - 23 Jul 2012
Cited by 37 | Viewed by 8094
Abstract
Nodal staging in breast cancer is a key predictor of prognosis. This paper presents the results of potential clinicopathological predictors of axillary lymph node involvement and develops an efficient prediction model to assist in predicting axillary lymph node metastases. Seventy patients with primary [...] Read more.
Nodal staging in breast cancer is a key predictor of prognosis. This paper presents the results of potential clinicopathological predictors of axillary lymph node involvement and develops an efficient prediction model to assist in predicting axillary lymph node metastases. Seventy patients with primary early breast cancer who underwent axillary dissection were evaluated. Univariate and multivariate logistic regression were performed to evaluate the association between clinicopathological factors and lymph node metastatic status. A logistic regression predictive model was built from 50 randomly selected patients; the model was also applied to the remaining 20 patients to assess its validity. Univariate analysis showed a significant relationship between lymph node involvement and absence of nm-23 (p = 0.010) and Kiss-1 (p = 0.001) expression. Absence of Kiss-1 remained significantly associated with positive axillary node status in the multivariate analysis (p = 0.018). Seven clinicopathological factors were involved in the multivariate logistic regression model: menopausal status, tumor size, ER, PR, HER2, nm-23 and Kiss-1. The model was accurate and discriminating, with an area under the receiver operating characteristic curve of 0.702 when applied to the validation group. Moreover, there is a need discover more specific candidate proteins and molecular biology tools to select more variables which should improve predictive accuracy. Full article
(This article belongs to the Special Issue Biomarkers and Nanosensors: New Approaches for Biology and Medicine)
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<p>ROC curve calculation for the logistic regression model applied to the modeling group (n = 50).</p> Full article ">
<p>Logistic regression model Scatter diagram (n = 50).</p> Full article ">
<p>Logistic regression model Scatter diagram (n = 20).</p> Full article ">
<p>ROC curve calculation for Logistic regression model applied to the validation group (n = 20).</p> Full article ">
8065 KiB  
Article
User Localization During Human-Robot Interaction
by F. Alonso-Martín, Javi F. Gorostiza, María Malfaz and Miguel A. Salichs
Sensors 2012, 12(7), 9913-9935; https://doi.org/10.3390/s120709913 - 23 Jul 2012
Cited by 13 | Viewed by 7873
Abstract
This paper presents a user localization system based on the fusion of visual information and sound source localization, implemented on a social robot called Maggie. One of the main requisites to obtain a natural interaction between human-human and human-robot is an adequate spatial [...] Read more.
This paper presents a user localization system based on the fusion of visual information and sound source localization, implemented on a social robot called Maggie. One of the main requisites to obtain a natural interaction between human-human and human-robot is an adequate spatial situation between the interlocutors, that is, to be orientated and situated at the right distance during the conversation in order to have a satisfactory communicative process. Our social robot uses a complete multimodal dialog system which manages the user-robot interaction during the communicative process. One of its main components is the presented user localization system. To determine the most suitable allocation of the robot in relation to the user, a proxemic study of the human-robot interaction is required, which is described in this paper. The study has been made with two groups of users: children, aged between 8 and 17, and adults. Finally, at the end of the paper, experimental results with the proposed multimodal dialog system are presented. Full article
(This article belongs to the Section Physical Sensors)
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<p>Our social robot, Maggie.</p> Full article ">
<p>Interaction with children aged from 8 to 10.</p> Full article ">
<p>Interaction with children aged over 10.</p> Full article ">
<p>Groupal interaction.</p> Full article ">
<p>Children mimic robot dance.</p> Full article ">
<p>Proxemic rules.</p> Full article ">
<p>Microphone layout in the robot Maggie.</p> Full article ">
<p>Microphones in the robot Maggie.</p> Full article ">
<p>Multimodal dialog system in AD.</p> Full article ">
1051 KiB  
Review
Foot Plantar Pressure Measurement System: A Review
by Abdul Hadi Abdul Razak, Aladin Zayegh, Rezaul K. Begg and Yufridin Wahab
Sensors 2012, 12(7), 9884-9912; https://doi.org/10.3390/s120709884 - 23 Jul 2012
Cited by 633 | Viewed by 65054
Abstract
Foot plantar pressure is the pressure field that acts between the foot and the support surface during everyday locomotor activities. Information derived from such pressure measures is important in gait and posture research for diagnosing lower limb problems, footwear design, sport biomechanics, injury [...] Read more.
Foot plantar pressure is the pressure field that acts between the foot and the support surface during everyday locomotor activities. Information derived from such pressure measures is important in gait and posture research for diagnosing lower limb problems, footwear design, sport biomechanics, injury prevention and other applications. This paper reviews foot plantar sensors characteristics as reported in the literature in addition to foot plantar pressure measurement systems applied to a variety of research problems. Strengths and limitations of current systems are discussed and a wireless foot plantar pressure system is proposed suitable for measuring high pressure distributions under the foot with high accuracy and reliability. The novel system is based on highly linear pressure sensors with no hysteresis. Full article
(This article belongs to the Section Physical Sensors)
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<p>A platform-based foot plantar pressure sensor emed<sup>®</sup> by Novel [<a href="#b24-sensors-12-09884" class="html-bibr">24</a>].</p> Full article ">
<p>A platform based foot plantar pressure sensor by Zebris Medical GmbH [<a href="#b25-sensors-12-09884" class="html-bibr">25</a>].</p> Full article ">
<p>An in-shoe based foot plantar pressure sensor by Pedar<sup>©</sup> Novel [<a href="#b24-sensors-12-09884" class="html-bibr">24</a>].</p> Full article ">
<p>An in-shoe based foot plantar pressure sensor F-Scan<sup>®</sup> System by Tekscan [<a href="#b26-sensors-12-09884" class="html-bibr">26</a>].</p> Full article ">
<p>Foot anatomical areas [<a href="#b30-sensors-12-09884" class="html-bibr">30</a>].</p> Full article ">
<p>Hysteresis caused by loading and unloading a pressure sensor usually measured at the 50% pressure range. Adopted from [<a href="#b32-sensors-12-09884" class="html-bibr">32</a>].</p> Full article ">
<p>Negligible hysteresis of MEMS-based pressure sensor [<a href="#b29-sensors-12-09884" class="html-bibr">29</a>].</p> Full article ">
<p>Effect of sensor sizing and placement.</p> Full article ">
<p>Example of erroneous readings due to sensor creep of Pedar<sup>®</sup> Insole. The curve is the error reading by the sensor and plotted line is the correct pressure values. Modified from [<a href="#b35-sensors-12-09884" class="html-bibr">35</a>].</p> Full article ">
2970 KiB  
Article
Electromagnetic Wave Propagation in Body Area Networks Using the Finite-Difference-Time-Domain Method
by Jonathan N. Bringuier and Raj Mittra
Sensors 2012, 12(7), 9862-9883; https://doi.org/10.3390/s120709862 - 23 Jul 2012
Cited by 9 | Viewed by 8369
Abstract
A rigorous full-wave solution, via the Finite-Difference-Time-Domain (FDTD) method, is performed in an attempt to obtain realistic communication channel models for on-body wireless transmission in Body-Area-Networks (BANs), which are local data networks using the human body as a propagation medium. The problem of [...] Read more.
A rigorous full-wave solution, via the Finite-Difference-Time-Domain (FDTD) method, is performed in an attempt to obtain realistic communication channel models for on-body wireless transmission in Body-Area-Networks (BANs), which are local data networks using the human body as a propagation medium. The problem of modeling the coupling between body mounted antennas is often not amenable to attack by hybrid techniques owing to the complex nature of the human body. For instance, the time-domain Green’s function approach becomes more involved when the antennas are not conformal. Furthermore, the human body is irregular in shape and has dispersion properties that are unique. One consequence of this is that we must resort to modeling the antenna network mounted on the body in its entirety, and the number of degrees of freedom (DoFs) can be on the order of billions. Even so, this type of problem can still be modeled by employing a parallel version of the FDTD algorithm running on a cluster. Lastly, we note that the results of rigorous simulation of BANs can serve as benchmarks for comparison with the abundance of measurement data. Full article
(This article belongs to the Special Issue Body Sensor Networks for Healthcare and Pervasive Applications)
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<p>3-layer ellipse model of the human torso with transmitting antenna at the front and receiving antenna at the back.</p> Full article ">
<p>Path loss around the cylindrical human trunk model at the source plane.</p> Full article ">
<p>Path loss around the cylindrical human trunk model 210 mm above source plane.</p> Full article ">
<p>Path loss around the cylindrical human trunk model 400 mm above source plane.</p> Full article ">
<p>Electric field distribution in the source plane.</p> Full article ">
<p>Electric field distribution on a vertical cut plane bisecting the cylindrical model.</p> Full article ">
<p>Path loss <span class="html-italic">versus</span> separation distance with receiving antenna at the source plane.</p> Full article ">
<p>Path loss <span class="html-italic">versus</span> separation distance with receiving antenna 210 mm above the source plane.</p> Full article ">
<p>Path loss <span class="html-italic">versus</span> separation distance with receiving antenna 400 mm above the source plane.</p> Full article ">
447 KiB  
Article
Characterizing the Moisture Content of Tea with Diffuse Reflectance Spectroscopy Using Wavelet Transform and Multivariate Analysis
by Xiaoli Li, Chuanqi Xie, Yong He, Zhengjun Qiu and Yanchao Zhang
Sensors 2012, 12(7), 9847-9861; https://doi.org/10.3390/s120709847 - 23 Jul 2012
Cited by 36 | Viewed by 7510
Abstract
Effects of the moisture content (MC) of tea on diffuse reflectance spectroscopy were investigated by integrated wavelet transform and multivariate analysis. A total of 738 representative samples, including fresh tea leaves, manufactured tea and partially processed tea were collected for spectral measurement in [...] Read more.
Effects of the moisture content (MC) of tea on diffuse reflectance spectroscopy were investigated by integrated wavelet transform and multivariate analysis. A total of 738 representative samples, including fresh tea leaves, manufactured tea and partially processed tea were collected for spectral measurement in the 325–1,075 nm range with a field portable spectroradiometer. Then wavelet transform (WT) and multivariate analysis were adopted for quantitative determination of the relationship between MC and spectral data. Three feature extraction methods including WT, principal component analysis (PCA) and kernel principal component analysis (KPCA) were used to explore the internal structure of spectral data. Comparison of those three methods indicated that the variables generated by WT could efficiently discover structural information of spectral data. Calibration involving seeking the relationship between MC and spectral data was executed by using regression analysis, including partial least squares regression, multiple linear regression and least square support vector machine. Results showed that there was a significant correlation between MC and spectral data (r = 0.991, RMSEP = 0.034). Moreover, the effective wavelengths for MC measurement were detected at range of 888–1,007 nm by wavelet transform. The results indicated that the diffuse reflectance spectroscopy of tea is highly correlated with MC. Full article
(This article belongs to the Section Chemical Sensors)
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<p>Vis/NIR diffuse reflectance spectroscopy of the samples.</p> Full article ">
<p>Structure of discrete wavelet decomposition at level 3.</p> Full article ">
<p>Wavelet decomposition coefficients by db5 at level 3.</p> Full article ">
<p>Energy distribution of wavelet coefficients.</p> Full article ">
<p>Description of tea samples in these new synthetic variable spaces, (<b>A</b>) in PCs space, (<b>B</b>) in KPCs space, and (<b>C</b>) in wavelet approximation coefficients (<span class="html-italic">cA<sub>3</sub></span>) space.</p> Full article ">
<p>Scatter plot of reference <span class="html-italic">vs.</span> predicted of the optimal MLR Model 6 (<b>a</b>) calibration result and (<b>b</b>) prediction result.</p> Full article ">
<p>B-coefficients of the optimal determination Model 6.</p> Full article ">
<p>Reconstruction of approximation at level 3 (<b>A</b>) Wavelet approximation coefficients at level 3 and (<b>B</b>) Reconstructed signals.</p> Full article ">
5124 KiB  
Article
Harnessing the Interaction Continuum for Subtle Assisted Living
by Manuel García-Herranz, Fernando Olivera, Pablo Haya and Xavier Alamán
Sensors 2012, 12(7), 9829-9846; https://doi.org/10.3390/s120709829 - 23 Jul 2012
Cited by 9 | Viewed by 7385
Abstract
People interact with each other in many levels of attention, intention and meaning. This Interaction Continuum is used daily to deal with different contexts, adapting the interaction to communication needs and available resources. Nevertheless, computer-supported interaction has mainly focused on the most direct, [...] Read more.
People interact with each other in many levels of attention, intention and meaning. This Interaction Continuum is used daily to deal with different contexts, adapting the interaction to communication needs and available resources. Nevertheless, computer-supported interaction has mainly focused on the most direct, explicit and intrusive types of human to human Interaction such as phone calls, emails, or video conferences. This paper presents the results of exploring and exploiting the potentials of undemanding interaction mechanisms, paying special attention to subtle communication and background interaction. As we argue the benefits of this type of interaction for people with special needs, we present a theoretical framework to define it and propose a proof of concept based on Augmented Objects and a color codification mechanism. Finally, we evaluate and analyze the strengths and limitations of such approach with people with cognitive disabilities. Full article
(This article belongs to the Special Issue Select papers from UCAmI 2011 - the 5th International Symposium on Ubiquitous Computing and Ambient Intelligence (UCAmI'11))
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<p>Interaction classification along the axis of attentional demand and initiative according to Ju and Leifer [<a href="#b18-sensors-12-09829" class="html-bibr">18</a>].</p> Full article ">
<p>Context-aware Communication schema considering sender (<span class="html-italic">A</span>), receiver (<span class="html-italic">B</span>), message (<span class="html-italic">m</span>), and the overlapping contexts of <span class="html-italic">A</span> and <span class="html-italic">B</span>.</p> Full article ">
<p>Our proposal for a communication classification along the axis of information and traffic. Traffic refers to the size of the message that is sent. The information axis considers the impact of that message in the receiver.</p> Full article ">
<p>Distant Human to Human Communication on an augmented Tupperware™.</p> Full article ">
<p>Available colors to establish person-color associations.</p> Full article ">
<p>Examples of the question cards used in the person-color association study.</p> Full article ">
<p>A prototype of an augmented Tupperware™ with the 4 × 4 button-RGB LED matrix integrated in its lid.</p> Full article ">
<p>Code for both cases of study (Symbol association to concepts and days for expiration).</p> Full article ">
633 KiB  
Communication
A Micro-Machined Gyroscope for Rotating Aircraft
by Qingwen Yan, Fuxue Zhang and Wei Zhang
Sensors 2012, 12(7), 9823-9828; https://doi.org/10.3390/s120709823 - 23 Jul 2012
Cited by 2 | Viewed by 6609
Abstract
In this paper we present recent work on the design, fabrication by silicon micromachining, and packaging of a new gyroscope for stabilizing the autopilot of rotating aircraft. It operates based on oscillation of the silicon pendulum between two torsion girders for detecting the [...] Read more.
In this paper we present recent work on the design, fabrication by silicon micromachining, and packaging of a new gyroscope for stabilizing the autopilot of rotating aircraft. It operates based on oscillation of the silicon pendulum between two torsion girders for detecting the Coriolis force. The oscillation of the pendulum is initiated by the rolling and deflecting motion of the rotating carrier. Therefore, the frequency and amplitude of the oscillation are proportional to the rolling frequency and deflecting angular rate of the rotating carrier, and are measured by the sensing electrodes. A modulated pulse with constant amplitude and unequal width is obtained by a linearizing process of the gyroscope output signal and used to control the deflection of the rotating aircraft. Experimental results show that the gyroscope has a resolution of 0.008 °/s and a bias of 56.18 °/h. Full article
(This article belongs to the Special Issue Ultra-Small Sensor Systems and Components)
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<p>(<b>a</b>) Structure of silicon pendulum; (<b>b</b>) Silicon pendulum picture; (<b>c</b>) Expanded solid model showing the silicon pendulum, electrode plate, lid and shell; (<b>d</b>) Gyroscope picture.</p> Full article ">
<p>(<b>a</b>) Waveform of the gyroscope signal, the linearized signal and the control signal in the first assumption; (<b>b</b>) Waveform of the gyroscope signal, the linearized signal and the control signal in the second assumption.</p> Full article ">
<p>(<b>a</b>) Frequency of gyroscope signal as a function of roll angular rate; (<b>b</b>) Amplitude of gyroscope signal as a function of yaw angular rate.</p> Full article ">
805 KiB  
Article
Ubiquitous Geo-Sensing for Context-Aware Analysis: Exploring Relationships between Environmental and Human Dynamics
by Günther Sagl, Thomas Blaschke, Euro Beinat and Bernd Resch
Sensors 2012, 12(7), 9800-9822; https://doi.org/10.3390/s120709800 - 18 Jul 2012
Cited by 27 | Viewed by 10768
Abstract
Ubiquitous geo-sensing enables context-aware analyses of physical and social phenomena, i.e., analyzing one phenomenon in the context of another. Although such context-aware analysis can potentially enable a more holistic understanding of spatio-temporal processes, it is rarely documented in the scientific literature yet. [...] Read more.
Ubiquitous geo-sensing enables context-aware analyses of physical and social phenomena, i.e., analyzing one phenomenon in the context of another. Although such context-aware analysis can potentially enable a more holistic understanding of spatio-temporal processes, it is rarely documented in the scientific literature yet. In this paper we analyzed the collective human behavior in the context of the weather. We therefore explored the complex relationships between these two spatio-temporal phenomena to provide novel insights into the dynamics of urban systems. Aggregated mobile phone data, which served as a proxy for collective human behavior, was linked with the weather data from climate stations in the case study area, the city of Udine, Northern Italy. To identify and characterize potential patterns within the weather-human relationships, we developed a hybrid approach which integrates several spatio-temporal statistical analysis methods. Thereby we show that explanatory factor analysis, when applied to a number of meteorological variables, can be used to differentiate between normal and adverse weather conditions. Further, we measured the strength of the relationship between the ‘global’ adverse weather conditions and the spatially explicit effective variations in user-generated mobile network traffic for three distinct periods using the Maximal Information Coefficient (MIC). The analyses result in three spatially referenced maps of MICs which reveal interesting insights into collective human dynamics in the context of weather, but also initiate several new scientific challenges. Full article
(This article belongs to the Special Issue Ubiquitous Sensing)
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<p>Study area: the urban environment of the city of Udine, Friuli Venetia Giulia Region, Italy; the red grid indicates the spatial resolution as 250 m × 250 m ‘pixels’ of the mobile network traffic.</p> Full article ">
<p>21 day-time series of total telecom traffic intensity, normal and adverse weather conditions in urban Udine; map: temporally accumulated telecom traffic intensity per 250 m ‘pixel’.</p> Full article ">
<p>Spectral correlation of normal and adverse weather conditions with telecom traffic intensity.</p> Full article ">
<p>21 days of adverse weather conditions and its loading meteorological components including three distinct adverse weather periods p1, p2, and p3.</p> Full article ">
<p>Adverse weather conditions (AWC) and effective variations in mobile network traffic: map of MICs (top), and temporal signatures of selected locations L (bottom) for the first (<b>a</b>); the second (<b>b</b>); and the third period (<b>c</b>); the temporal signatures are averaged if more than one ‘pixel’ is involved.</p> Full article ">
<p>Adverse weather conditions (AWC) and effective variations in mobile network traffic: map of MICs (top), and temporal signatures of selected locations L (bottom) for the first (<b>a</b>); the second (<b>b</b>); and the third period (<b>c</b>); the temporal signatures are averaged if more than one ‘pixel’ is involved.</p> Full article ">
388 KiB  
Article
Sensitivity of a Label-Free Guided-Mode Resonant Optical Biosensor with Different Modes
by Qi Wang, Dawei Zhang, Huiyin Yang, Chunxian Tao, Yuanshen Huang, Songlin Zhuang and Ting Mei
Sensors 2012, 12(7), 9791-9799; https://doi.org/10.3390/s120709791 - 18 Jul 2012
Cited by 17 | Viewed by 7168
Abstract
Sensitivity is a key factor in the performance of a sensor. To achieve maximum guided-mode resonant optical biosensor sensitivity, a comparison of biosensor sensitivity for Transverse Electric (TE) and Transverse Magnetic (TM) modes based on the distribution of electric fields is presented in [...] Read more.
Sensitivity is a key factor in the performance of a sensor. To achieve maximum guided-mode resonant optical biosensor sensitivity, a comparison of biosensor sensitivity for Transverse Electric (TE) and Transverse Magnetic (TM) modes based on the distribution of electric fields is presented in this article. A label-free guided-mode resonant optical biosensor is designed using the quarter-wave anti-reflection method to reflect only a narrow band of wavelengths modulated by the adsorption of a biochemical material on the sensor surface at the reflected frequency. With the distribution of electric fields simulated according to the Rigorous Coupled Wave Analysis (RCWA) theory, it is found that the full width at half maximum of the TM mode is (~4 nm) narrower than that of the TE mode (~20 nm), and the surface sensitivity of the TE mode incident light is three times that of the TM mode. It is proposed in this article that the light mode plays an important role in the sensitivity of guided-mode resonant biosensors. Full article
(This article belongs to the Section Biosensors)
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<p>Structure of the GMRF The parameters are n<sub>h</sub> = n<sub>w</sub> = 1.98 (HfO<sub>2</sub>), n<sub>l</sub> = n<sub>c</sub> = 1.0 (air), n<sub>s</sub> = 1.52 (quartz glass), Λ = 500 nm, d<sub>w</sub> = 101 nm, d<sub>g</sub> = 120 nm.</p> Full article ">
<p>Electric field distribution of TE mode at different wavelengths. (<b>a</b>) Electric field distribution at the wavelength of 798 nm with TE mode incident into the GMRF. (<b>b</b>) Wavelength at 788 nm. (<b>c</b>) Wavelength at 808 nm. (<b>d</b>) Wavelength at 778 nm. (<b>e</b>) Wavelength at 818 nm.</p> Full article ">
<p>Electric field distribution of TM mode at different wavelengths. (<b>a</b>) Electric field distribution at the wavelength of 766 nm with TM mode incident into the GMRF. (<b>b</b>) Wavelength at 763 nm. (<b>c</b>) Wavelength at 769 nm. (<b>d</b>) Wavelength at 760 nm. (<b>e</b>) Wavelength at 772 nm.</p> Full article ">
<p>Sensitivity of the TE mode and TM mode.</p> Full article ">
1017 KiB  
Article
Correcting the Temperature Influence on Soil Capacitance Sensors Using Diurnal Temperature and Water Content Cycles
by André Chanzy, Jean-Claude Gaudu and Olivier Marloie
Sensors 2012, 12(7), 9773-9790; https://doi.org/10.3390/s120709773 - 18 Jul 2012
Cited by 35 | Viewed by 14331
Abstract
The influence of temperature on the dielectric permittivity of soil is the result of counteracting effect that depends on the soil’s composition and mineralogy. In this paper, laboratory experiments showed that for a given water content, the soil dielectric permittivity was linearly related [...] Read more.
The influence of temperature on the dielectric permittivity of soil is the result of counteracting effect that depends on the soil’s composition and mineralogy. In this paper, laboratory experiments showed that for a given water content, the soil dielectric permittivity was linearly related to the temperature, with a slope (α) that varied between samples taken in the same soil. These variations are difficult to predict and therefore, a simple and straightforward algorithm was designed to estimate α based on the diurnal patterns of both the measured dielectric permittivity and the soil temperature. The underlying idea is to assume that soil water content variations can be known with a reasonable accuracy over an appropriate time window within a day. This allows determining the contribution of the soil water content to the dielectric permittivity variations and then, the difference with the observed measurements is attributed to the soil temperature. Implementation of the correction methods in a large number of experiments significantly improved the physical meaning of the temporal evolution of the soil water content as the daily cycles for probes located near the surface or the long-term variations for more deeply installed probes. Full article
(This article belongs to the Section Physical Sensors)
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Graphical abstract

Graphical abstract
Full article ">
<p>The HMS 9000 electrode geometry.</p> Full article ">
<p>Concurrent simulated variations of soil water content and soil temperature during a drying cycle as calculated by the TEC model for the silt loam soil (CO-SiL). Solid grids at 48, 72 and 96 h correspond to midnight.</p> Full article ">
<p>Concurrent simulated variations of soil water content and soil temperature during a drying cycle as calculated by the TEC model for the silt loam soil (CO-SiL). Solid grids at 120, 144, and 168 h correspond to midnight.</p> Full article ">
<p>Absolute difference between the retrieved α (K<sup>−1</sup>) at several depths (2.5, 20 and 40 cm) and the reference α (α<sub>ref</sub>) determined from the data simulated by the TEC model using the four methods (Cm, Ce, Cme, Cd). Each graph corresponds to a given soil. NA is given when <span class="html-italic">α</span> could not be determined. SiL and SiCL correspond to soils having a Silt Loam and Silty Clay Loam texture, respectively.</p> Full article ">
<p>Error in α as a function of depth considering the Cme and Cd methods. Different measurement error scenarios given in the legend for temperature (σ<sub>T</sub>) and the dielectric permittivity (σ<span class="html-italic"><sub>ε</sub></span>) are considered.</p> Full article ">
<p>Soil water content measured by the HMS9000 located at a 2.5-cm depth. The probe calibration was done either with the unprocessed measurement (dotted line) or with the measurement corrected by the temperature effect (solid line). Solid grids at 134, 135 … correspond to midnight.</p> Full article ">
<p>Temperature Sensitivity coefficient α as a function of the soil dielectric permittivity obtained with the DECAGON EC-10 probe installed at 2.5 cm depth at the INRA-Avignon observatory. Measurements were taken during the bare soil period of the sequence 2 with the sensor P3 (<a href="#t2-sensors-12-09773" class="html-table">Table 2</a>).</p> Full article ">
<p>Soil water content measured by an EC-10 installed at a 2.5-cm depth. The probe calibration was done either with the unprocessed measurement (dotted line) or with the measurement corrected by the temperature effect (solid line). Vertical solid grids correspond at midnight.</p> Full article ">
<p>Soil water content measured by a HMS 9000 capacitance probe located at a 65-cm depth and by Neutron and gravimetric methods. Temperature coefficient <span class="html-italic">α</span> was determined by the Cd method. Error bars corresponds to the standard deviation of the measurements.</p> Full article ">
620 KiB  
Article
Investigation of Interactive Effects on Water Flow and Solute Transport in Sandy Loam Soil Using Time Domain Reflectometry
by Hasan Merdun
Sensors 2012, 12(7), 9749-9772; https://doi.org/10.3390/s120709749 - 18 Jul 2012
Cited by 3 | Viewed by 7140
Abstract
Surface-applied chemicals move through the unsaturated zone with complex flow and transport processes due to soil heterogeneity and reach the saturated zone, resulting in groundwater contamination. Such complex processes need to be studied by advanced measurement and modeling techniques to protect soil and [...] Read more.
Surface-applied chemicals move through the unsaturated zone with complex flow and transport processes due to soil heterogeneity and reach the saturated zone, resulting in groundwater contamination. Such complex processes need to be studied by advanced measurement and modeling techniques to protect soil and water resources from contamination. In this study, the interactive effects of factors like soil structure, initial soil water content (SWC), and application rate on preferential flow and transport were studied in a sandy loam field soil using measurement (by time domain reflectometry (TDR)) and modeling (by MACRO and VS2DTI) techniques. In addition, statistical analyses were performed to compare the means of the measured and modeled SWC and EC, and solute transport parameters (pore water velocity and dispersion coefficient) in 12 treatments. Research results showed that even though the effects of soil structural conditions on water and solute transport were not so clear, the applied solution moved lower depths in the profiles of wet versus dry initial SWC and high application rate versus low application rates. The effects of soil structure and initial SWC on water and solute movement could be differentiated under the interactive conditions, but the effects of the application rates were difficult to differentiate under different soil structural and initial SWC conditions. Modeling results showed that MACRO had somewhat better performance than VS2DTI in the estimation of SWC and EC with space and time, but overall both models had relatively low performances. The means of SWC, EC, and solute transport parameters of the 12 treatments were divided into some groups based on the statistical analyses, indicating different flow and transport characteristics or a certain degree nonuniform or preferential flow and transport in the soil. Conducting field experiments with more interactive factors and applying the models with different approaches may allow better understanding of flow and transport processes in addition to the simulations of them in the unsaturated zone. Full article
(This article belongs to the Section Physical Sensors)
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<p>A sketch of the experimental design. Connection of a single thermocouple to the datalogger and connection of a single probe to the multiplexer are shown in the skecth to make presentation simple.</p> Full article ">
<p>Spatial and temporal variability of soil water content (SWC) and electrical conductivity (EC) in the treatment of Sandy loam + Undisturbed + Dry + Low. The symbols of ○, ▲, and ■ represent the measured and model (MACRO and VS2DTI; values, respectively. CME and RMSE are the coeficient of model efficiency and the root mean square error, respectively.</p> Full article ">
<p>Spatial and temporal variability of soil water content (SWC) and electrical conductivity (EC) in the treatment of Sandy loam + Undisturbed + Dry + High. The symbols of ○, ▲, and ■ represent the measured and model (MACRO and VS2DTI; values, respectively. CME and RMSE are the coeficient of model efficiency and the root mean square error, respectively.</p> Full article ">
<p>The variation of soil water content (SWC) and electrical conductivity (EC) with depth at 1 h of the experiment in the 8 treatments. The initial, measured, and model (MACRO and VS2DTI) values are exhibited by symbols ★, ○, ▲, and ■, respectively. CME and RMSE are the coeficient of model efficiency and the root mean square error, respectively.</p> Full article ">
<p>The variation of soil water content (SWC) and electrical conductivity (EC) with depth at 3 h of the experiment in the 8 treatments. The initial, measured, and model (MACRO and VS2DTI) values are exhibited by symbols ★, ○, ▲, and ■, respectively. CME and RMSE are the coeficient of model efficiency and the root mean square error, respectively.</p> Full article ">
<p>The variation of soil water content (SWC) and electrical conductivity (EC) with depth at 10 h of the experiment in the 8 treatments. The initial, measured, and model (MACRO and VS2DTI) values are exhibited by symbols ★, ○, ▲, and ■, respectively. CME and RMSE are the coeficient of model efficiency and the root mean square error, respectively.</p> Full article ">
2807 KiB  
Article
SEMAT — The Next Generation of Inexpensive Marine Environmental Monitoring and Measurement Systems
by Jarrod Trevathan, Ron Johnstone, Tony Chiffings, Ian Atkinson, Neil Bergmann, Wayne Read, Susan Theiss, Trina Myers and Tom Stevens
Sensors 2012, 12(7), 9711-9748; https://doi.org/10.3390/s120709711 - 18 Jul 2012
Cited by 48 | Viewed by 12704
Abstract
There is an increasing need for environmental measurement systems to further science and thereby lead to improved policies for sustainable management. Marine environments are particularly hostile and extremely difficult for deploying sensitive measurement systems. As a consequence the need for data is greatest [...] Read more.
There is an increasing need for environmental measurement systems to further science and thereby lead to improved policies for sustainable management. Marine environments are particularly hostile and extremely difficult for deploying sensitive measurement systems. As a consequence the need for data is greatest in marine environments, particularly in the developing economies/regions. Expense is typically the most significant limiting factor in the number of measurement systems that can be deployed, although technical complexity and the consequent high level of technical skill required for deployment and servicing runs a close second. This paper describes the Smart Environmental Monitoring and Analysis Technologies (SEMAT) project and the present development of the SEMAT technology. SEMAT is a “smart” wireless sensor network that uses a commodity-based approach for selecting technologies most appropriate to the scientifically driven marine research and monitoring domain/field. This approach allows for significantly cheaper environmental observation systems that cover a larger geographical area and can therefore collect more representative data. We describe SEMAT’s goals, which include: (1) The ability to adapt and evolve; (2) Underwater wireless communications; (3) Short-range wireless power transmission; (4) Plug and play components; (5) Minimal deployment expertise; (6) Near real-time analysis tools; and (7) Intelligent sensors. This paper illustrates how the capacity of the system has been improved over three iterations towards realising these goals. The result is an inexpensive and flexible system that is ideal for short-term deployments in shallow coastal and other aquatic environments. Full article
(This article belongs to the Section Sensor Networks)
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<p>The complete SEMAT system.</p> Full article ">
<p>The cost spectrum for environmental monitoring systems in terms of sensor expense.</p> Full article ">
<p>The allocation of tasks across the SEMAT project.</p> Full article ">
<p>The SEMAT Mk1 prototype buoy. Examples of the gateway and surface nodes and the system deployed at Moreton Bay, Australia.</p> Full article ">
<p>Tidal Turbines. From left to right are the (<b>a</b>) Swanturbine<b><sup>®</sup></b>, (<b>b</b>) By-ostream<b><sup>®</sup></b>, (<b>c</b>) Savonius<b><sup>®</sup></b>, and (<b>d</b>) Gorlov<b><sup>®</sup></b>.</p> Full article ">
<p>The SEMAT Mk2 prototype buoy. The illustration on the left shows the Mk2 <span class="html-italic">in-situ</span> at Deception Bay, the illustration on the right presents the Mk2's internal components.</p> Full article ">
<p>Locations of the SEMAT Mk2 buoys within Deception Bay. Each buoy was labelled A, B, C, D and E respectively. All buoys were identical except for Node A, which contained an above water light sensor. The base station was located on Sandstone Point (indicated by the yellow pin). The buoy ranges from the base station were as follows: Node A—1.4 km, Node B—1.3 km, Node C—1.0 km, Node D—1.4 km and Node E—1.7 km.</p> Full article ">
<p>The conceptual setup for the Deception Bay deployment.</p> Full article ">
<p>The SEMAT Mk2 base station on Sandstone Point at Deception Bay.</p> Full article ">
1201 KiB  
Article
Design and Analysis of a Compact Precision Positioning Platform Integrating Strain Gauges and the Piezoactuator
by Hu Huang, Hongwei Zhao, Zhaojun Yang, Zunqiang Fan, Shunguang Wan, Chengli Shi and Zhichao Ma
Sensors 2012, 12(7), 9697-9710; https://doi.org/10.3390/s120709697 - 17 Jul 2012
Cited by 18 | Viewed by 8584
Abstract
Miniaturization precision positioning platforms are needed for in situ nanomechanical test applications. This paper proposes a compact precision positioning platform integrating strain gauges and the piezoactuator. Effects of geometric parameters of two parallel plates on Von Mises stress distribution as well as static [...] Read more.
Miniaturization precision positioning platforms are needed for in situ nanomechanical test applications. This paper proposes a compact precision positioning platform integrating strain gauges and the piezoactuator. Effects of geometric parameters of two parallel plates on Von Mises stress distribution as well as static and dynamic characteristics of the platform were studied by the finite element method. Results of the calibration experiment indicate that the strain gauge sensor has good linearity and its sensitivity is about 0.0468 mV/μm. A closed-loop control system was established to solve the problem of nonlinearity of the platform. Experimental results demonstrate that for the displacement control process, both the displacement increasing portion and the decreasing portion have good linearity, verifying that the control system is available. The developed platform has a compact structure but can realize displacement measurement with the embedded strain gauges, which is useful for the closed-loop control and structure miniaturization of piezo devices. It has potential applications in nanoindentation and nanoscratch tests, especially in the field of in situ nanomechanical testing which requires compact structures. Full article
(This article belongs to the Special Issue Ultra-Small Sensor Systems and Components)
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<p>Schematic diagram of the developed platform.</p> Full article ">
<p>Wheatstone bridge.</p> Full article ">
<p>The principle of the strain gauge.</p> Full article ">
<p>The simplified upper plate with strain gauges.</p> Full article ">
<p>The simplified model of the strain gauge sensor.</p> Full article ">
<p>Von Mises stress distribution along the elastic plate with (<b>a</b>) different length <span class="html-italic">l</span><sub>1</sub>; (<b>b</b>) different thickness <span class="html-italic">t</span><sub>1</sub>; (<b>c</b>) different width <span class="html-italic">w</span><sub>1</sub>.</p> Full article ">
<p>The mesh model of the flexure hinge frame.</p> Full article ">
<p>Stress distribution of the flexure hinge frame.</p> Full article ">
<p>The first three order mode shapes of the precision positioning platform.</p> Full article ">
350 KiB  
Article
A Novel Instrumentation Circuit for Electrochemical Measurements
by Li-Te Yin, Hung-Yu Wang, Yang-Chiuan Lin and Wen-Chung Huang
Sensors 2012, 12(7), 9687-9696; https://doi.org/10.3390/s120709687 - 17 Jul 2012
Cited by 7 | Viewed by 6232
Abstract
In this paper, a novel signal processing circuit which can be used for the measurement of H+ ion and urea concentration is presented. A potentiometric method is used to detect the concentrations of H+ ions and urea by using H+ [...] Read more.
In this paper, a novel signal processing circuit which can be used for the measurement of H+ ion and urea concentration is presented. A potentiometric method is used to detect the concentrations of H+ ions and urea by using H+ ion-selective electrodes and urea electrodes, respectively. The experimental data shows that this measuring structure has a linear pH response for the concentration range within pH 2 and 12, and the dynamic range for urea concentration measurement is in the range of 0.25 to 64 mg/dL. The designed instrumentation circuit possesses a calibration function and it can be applied to different sensing electrodes for electrochemical analysis. It possesses the advantageous properties of being multi-purpose, easy calibration and low cost. Full article
(This article belongs to the Section Biosensors)
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<p>Electrode structure of ion-contact type.</p> Full article ">
<p>Practical pH electrode connected with a coaxial wire.</p> Full article ">
<p>The system structure for potential measurement.</p> Full article ">
<p>Instrumentation amplifier circuit.</p> Full article ">
<p>The internal operation of P89C51 for pH measurement.</p> Full article ">
<p>Measurement result of urea concentration.</p> Full article ">
<p>The internal operation of P89C51 for urea measurement.</p> Full article ">
<p>The designed electrochemical sensing instrumentation.</p> Full article ">
<p>The plot of output voltage for different pH solutions.</p> Full article ">
1201 KiB  
Article
A Simplified Baseband Prefilter Model with Adaptive Kalman Filter for Ultra-Tight COMPASS/INS Integration
by Yong Luo, Wenqi Wu, Ravindra Babu, Kanghua Tang and Bing Luo
Sensors 2012, 12(7), 9666-9686; https://doi.org/10.3390/s120709666 - 17 Jul 2012
Cited by 12 | Viewed by 7542
Abstract
COMPASS is an indigenously developed Chinese global navigation satellite system and will share many features in common with GPS (Global Positioning System). Since the ultra-tight GPS/INS (Inertial Navigation System) integration shows its advantage over independent GPS receivers in many scenarios, the federated ultra-tight [...] Read more.
COMPASS is an indigenously developed Chinese global navigation satellite system and will share many features in common with GPS (Global Positioning System). Since the ultra-tight GPS/INS (Inertial Navigation System) integration shows its advantage over independent GPS receivers in many scenarios, the federated ultra-tight COMPASS/INS integration has been investigated in this paper, particularly, by proposing a simplified prefilter model. Compared with a traditional prefilter model, the state space of this simplified system contains only carrier phase, carrier frequency and carrier frequency rate tracking errors. A two-quadrant arctangent discriminator output is used as a measurement. Since the code tracking error related parameters were excluded from the state space of traditional prefilter models, the code/carrier divergence would destroy the carrier tracking process, and therefore an adaptive Kalman filter algorithm tuning process noise covariance matrix based on state correction sequence was incorporated to compensate for the divergence. The federated ultra-tight COMPASS/INS integration was implemented with a hardware COMPASS intermediate frequency (IF), and INS’s accelerometers and gyroscopes signal sampling system. Field and simulation test results showed almost similar tracking and navigation performances for both the traditional prefilter model and the proposed system; however, the latter largely decreased the computational load. Full article
(This article belongs to the Section Physical Sensors)
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<p>Central design of ultra-tight GPS/INS integration.</p> Full article ">
<p>Federated design of ultra-tight GPS/INS integration.</p> Full article ">
<p>Federated ultra-tight GPS/INS integration with one channel in detail.</p> Full article ">
<p>Flow diagram for federated COMPASS/INS integration complementation with the simplified prefilter model and adaptive Kalman filter.</p> Full article ">
<p>COMPASS IF data and INS data collection process with GNSS/INS hardware simulator.</p> Full article ">
<p>(<b>a</b>) The reference trajectory for simulation; (<b>b</b>) COMPSS satellite sky-plot in simulation test.</p> Full article ">
<p>(<b>a</b>) The reference trajectory for simulation; (<b>b</b>) COMPSS satellite sky-plot in simulation test.</p> Full article ">
<p>(<b>a</b>) Tracking performance comparison for SV04; (<b>b</b>) Tracking performance comparison for SV05.</p> Full article ">
<p>(<b>a</b>) Velocity estimation errors of S-AKF and T-KF in ECEF frame; (<b>b</b>) Position estimation errors of S-AKF and T-KF in ECEF frame.</p> Full article ">
<p>COMPASS IF data and IMU data collection process in field environment.</p> Full article ">
384 KiB  
Review
A Survey on Gas Sensing Technology
by Xiao Liu, Sitian Cheng, Hong Liu, Sha Hu, Daqiang Zhang and Huansheng Ning
Sensors 2012, 12(7), 9635-9665; https://doi.org/10.3390/s120709635 - 16 Jul 2012
Cited by 1197 | Viewed by 44790
Abstract
Sensing technology has been widely investigated and utilized for gas detection. Due to the different applicability and inherent limitations of different gas sensing technologies, researchers have been working on different scenarios with enhanced gas sensor calibration. This paper reviews the descriptions, evaluation, comparison [...] Read more.
Sensing technology has been widely investigated and utilized for gas detection. Due to the different applicability and inherent limitations of different gas sensing technologies, researchers have been working on different scenarios with enhanced gas sensor calibration. This paper reviews the descriptions, evaluation, comparison and recent developments in existing gas sensing technologies. A classification of sensing technologies is given, based on the variation of electrical and other properties. Detailed introduction to sensing methods based on electrical variation is discussed through further classification according to sensing materials, including metal oxide semiconductors, polymers, carbon nanotubes, and moisture absorbing materials. Methods based on other kinds of variations such as optical, calorimetric, acoustic and gas-chromatographic, are presented in a general way. Several suggestions related to future development are also discussed. Furthermore, this paper focuses on sensitivity and selectivity for performance indicators to compare different sensing technologies, analyzes the factors that influence these two indicators, and lists several corresponding improved approaches. Full article
(This article belongs to the Section Chemical Sensors)
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<p>Classification of gas sensing methods.</p> Full article ">
<p>A thermostatic cycle of a sensitive element for CO and CH<sub>4</sub>.</p> Full article ">
<p>Sensor system (<b>a</b>) integrated with wireless module and (<b>b</b>) based on wireless transducer.</p> Full article ">
<p>IR-source gas sensors (<b>a</b>) based on the basic absorption spectrometry and (<b>b</b>) with reference filter/detector.</p> Full article ">
<p>Catalytic sensor (<b>a</b>) schematic diagram and (<b>b</b>) configuration of ceramic bead.</p> Full article ">
<p>Method of ultrasonic detection.</p> Full article ">
<p>Absorption period of pre-concentration technology.</p> Full article ">
2278 KiB  
Article
A Low-Cost Sensor Buoy System for Monitoring Shallow Marine Environments
by Cristina Albaladejo, Fulgencio Soto, Roque Torres, Pedro Sánchez and Juan A. López
Sensors 2012, 12(7), 9613-9634; https://doi.org/10.3390/s120709613 - 16 Jul 2012
Cited by 91 | Viewed by 18241
Abstract
Monitoring of marine ecosystems is essential to identify the parameters that determine their condition. The data derived from the sensors used to monitor them are a fundamental source for the development of mathematical models with which to predict the behaviour of conditions of [...] Read more.
Monitoring of marine ecosystems is essential to identify the parameters that determine their condition. The data derived from the sensors used to monitor them are a fundamental source for the development of mathematical models with which to predict the behaviour of conditions of the water, the sea bed and the living creatures inhabiting it. This paper is intended to explain and illustrate a design and implementation for a new multisensor monitoring buoy system. The system design is based on a number of fundamental requirements that set it apart from other recent proposals: low cost of implementation, the possibility of application in coastal shallow-water marine environments, suitable dimensions for deployment and stability of the sensor system in a shifting environment like the sea bed, and total autonomy of power supply and data recording. The buoy system has successfully performed remote monitoring of temperature and marine pressure (SBE 39 sensor), temperature (MCP9700 sensor) and atmospheric pressure (YOUNG 61302L sensor). The above requirements have been satisfactorily validated by operational trials in a marine environment. The proposed buoy sensor system thus seems to offer a broad range of applications. Full article
(This article belongs to the Section Remote Sensors)
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<p>Buoy components.</p> Full article ">
<p>Mechanical structure of the buoy and its characteristics, including the adopted protocol, antenna and range.</p> Full article ">
<p>Block diagram.</p> Full article ">
<p>Sensor buoy function state machine.</p> Full article ">
<p>The buoy's current consumption in each of these states.</p> Full article ">
<p>Location and deployment of tests in Cartagena Port.</p> Full article ">
<p>Part of the data collected by the sensor buoy.</p> Full article ">
<p>Coverage trials in the Mar Menor.</p> Full article ">
<p>The boat used for the deployment trials in the Mar Menor.</p> Full article ">
320 KiB  
Article
Screening of Stepping Forces in an Arthritic Rat Model Using a Novel Analgesic Meter and Data Acquisition System
by Mun Fei Yam, Mariam Ahmad, Lip Yee Por, Lee Fung Ang, Rusliza Basir and Mohd. Zaini Asmawi
Sensors 2012, 12(7), 9603-9612; https://doi.org/10.3390/s120709603 - 16 Jul 2012
Cited by 1 | Viewed by 6108
Abstract
The stepping forces of normal and Freund Complete Adjuvant (FCA)-induced arthritic rats were studied in vivo using a proposed novel analgesic meter. An infrared charge-coupled device (CCD) camera and a data acquisition system were incorporated into the analgesic meter to determine and measure [...] Read more.
The stepping forces of normal and Freund Complete Adjuvant (FCA)-induced arthritic rats were studied in vivo using a proposed novel analgesic meter. An infrared charge-coupled device (CCD) camera and a data acquisition system were incorporated into the analgesic meter to determine and measure the weight of loads on the right hind paw before and after induction of arthritis by FCA injection into the paw cavity. FCA injection resulted in a significant reduction in the stepping force of the affected hind paw. The stepping force decreased to the minimum level on day 4 after the injection and then gradually increased up to day 25. Oral administration of prednisolone significantly increased the stepping forces of FCA-induced arthritic rats on days 14 and 21. These results suggest that the novel device is an effective tool for measuring the arthritic pain in in vivo studies even though walking is a dynamic condition. Full article
(This article belongs to the Section Biosensors)
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<p>Walking steps of rat were captured by CCD camera, (<b>a</b>) and (<b>b</b>) showed the image of front and hind paws. Typical stepping force <span class="html-italic">versus</span> time curves constructed and for normal hind and front paws before the induction of arthritis (<b>c</b>,<b>d</b>), after the induction of arthritis by FCA injection (<b>e</b>) and in the FCA-induced arthritic rats treated with prednisolone (<b>f</b>). In normal rats, the stepping force produced by the hind paw was always higher than that of the front paw (c,d). After the induction of arthritis, the stepping force produced by the affected hind paw decreased (e). There was an improvement in the stepping force in rats treated with prednisolone (f).</p> Full article ">
<p>Comparison of stepping forces. (<b>a</b>) Left and right hind paws, (<b>b</b>) left and right front paws, (<b>c</b>) left front and hind paws, (<b>d</b>) right front and hind paws. (N = 6) * <span class="html-italic">P</span> &lt; 0.05, ** <span class="html-italic">P</span> &lt; 0.01, *** <span class="html-italic">P</span> &lt; 0.001 between the groups.</p> Full article ">
<p>Comparison of stepping forces of the left and right, front and hind paws of fasting and non-fasting rats.</p> Full article ">
<p>Anti-inflammatory effect of prednisolone on FCA-induced arthritic rats. (N = 6) * <span class="html-italic">P</span> &lt; 0.05, ** <span class="html-italic">P</span> &lt; 0.01, *** <span class="html-italic">P</span> &lt; 0.001 compared to the control group.</p> Full article ">
<p>Stepping forces of right hind paws of FCA-induced arthritic rats. (<b>a</b>) Untreated, (<b>b</b>) orally treated with prednisolone at 10 mg/kg per day, (<b>c</b>) orally treated with prednisolone at 5 mg/kg per day, (<b>d</b>) orally treated daily with prednisolone at 2.5 mg/kg per day. (N = 6) * <span class="html-italic">P</span> &lt; 0.05, ** <span class="html-italic">P</span> &lt; 0.01, *** <span class="html-italic">P</span> &lt; 0.001 compared to the stepping force of the normal left hind paw in the same group.</p> Full article ">
765 KiB  
Article
Study on Elastic Helical TDR Sensing Cable for Distributed Deformation Detection
by Renyuan Tong, Ming Li and Qing Li
Sensors 2012, 12(7), 9586-9602; https://doi.org/10.3390/s120709586 - 13 Jul 2012
Cited by 5 | Viewed by 7161
Abstract
In order to detect distributed ground surface deformation, an elastic helical structure Time Domain Reflectometry (TDR) sensing cable is shown in this paper. This special sensing cable consists of three parts: a silicone rubber rope in the center; a couple of parallel wires [...] Read more.
In order to detect distributed ground surface deformation, an elastic helical structure Time Domain Reflectometry (TDR) sensing cable is shown in this paper. This special sensing cable consists of three parts: a silicone rubber rope in the center; a couple of parallel wires coiling around the rope; a silicone rubber pipe covering the sensing cable. By analyzing the relationship between the impedance and the structure of the sensing cable, the impedance model shows that the sensing cable impedance will increase when the cable is stretched. This specific characteristic is verified in the cable stretching experiment which is the base of TDR sensing technology. The TDR experiment shows that a positive reflected signal is created at the stretching deformation point on the sensing cable. The results show that the deformation section length and the stretching elongation will both affect the amplitude of the reflected signal. Finally, the deformation locating experiments show that the sensing cable can accurately detect the deformation point position on the sensing cable. Full article
(This article belongs to the Section Physical Sensors)
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<p>TDR measurement system.</p> Full article ">
<p>Coaxial cable cross-sectional sharp deformation.</p> Full article ">
<p>Stretch deformation.</p> Full article ">
<p>. Structure of elastic helical TDR sensing cable.</p> Full article ">
<p>. Parallel wires structure.</p> Full article ">
<p>. TDR sensing cable when stretched.</p> Full article ">
<p>. Transmission-line model.</p> Full article ">
<p>. Electric field distribution.</p> Full article ">
<p>Relationship curve between <span class="html-italic">Δd</span> and <span class="html-italic">Z<sub>C</sub></span>.</p> Full article ">
5709 KiB  
Article
Adaptive UAV Attitude Estimation Employing Unscented Kalman Filter, FOAM and Low-Cost MEMS Sensors
by Héctor García De Marina, Felipe Espinosa and Carlos Santos
Sensors 2012, 12(7), 9566-9585; https://doi.org/10.3390/s120709566 - 13 Jul 2012
Cited by 51 | Viewed by 10242
Abstract
Navigation employing low cost MicroElectroMechanical Systems (MEMS) sensors in Unmanned Aerial Vehicles (UAVs) is an uprising challenge. One important part of this navigation is the right estimation of the attitude angles. Most of the existent algorithms handle the sensor readings in a fixed [...] Read more.
Navigation employing low cost MicroElectroMechanical Systems (MEMS) sensors in Unmanned Aerial Vehicles (UAVs) is an uprising challenge. One important part of this navigation is the right estimation of the attitude angles. Most of the existent algorithms handle the sensor readings in a fixed way, leading to large errors in different mission stages like take-off aerobatic maneuvers. This paper presents an adaptive method to estimate these angles using off-the-shelf components. This paper introduces an Attitude Heading Reference System (AHRS) based on the Unscented Kalman Filter (UKF) using the Fast Optimal Attitude Matrix (FOAM) algorithm as the observation model. The performance of the method is assessed through simulations. Moreover, field experiments are presented using a real fixed-wing UAV. The proposed low cost solution, implemented in a microcontroller, shows a satisfactory real time performance. Full article
(This article belongs to the Special Issue Transducer Systems)
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<p>Mentor Multiplex aircraft modified by the authors to be a UAV.</p> Full article ">
<p>Axes and coordinate definitions.</p> Full article ">
<p>Algorithm block diagram. WMM is the World Magnetic Model and the GPS velocity is employed for subtract the centripetal acceleration.</p> Full article ">
<p>Block diagram of the simulation environment.</p> Full article ">
<p>Aerobatics scenario with two <span class="html-italic">loopings</span>.</p> Full article ">
<p>Estimation of the biases of the gyroscopes, employing TRIAD at the left and FOAM at the right during the aerobatics simulation shown in <a href="#f5-sensors-12-09566" class="html-fig">Figure 5</a>.</p> Full article ">
<p>Pitch angle estimation during the aerobatics, employing TRIAD in the left and FOAM in the right during the aerobatics simulation shown in <a href="#f5-sensors-12-09566" class="html-fig">Figure 5</a>.</p> Full article ">
<p>Roll angle estimation during the aerobatics, employing TRIAD in the left and FOAM in the right during the aerobatics simulation shown in <a href="#f5-sensors-12-09566" class="html-fig">Figure 5</a>.</p> Full article ">
<p>Accelerometers readings and evolution of the FOAM weights during the aerobatics simulation shown in <a href="#f5-sensors-12-09566" class="html-fig">Figure 5</a>.</p> Full article ">
1349 KiB  
Article
Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet Transformation
by Donghui Mu, Dongju Chen, Jinwei Fan, Xiaofeng Wang and Feihu Zhang
Sensors 2012, 12(7), 9551-9565; https://doi.org/10.3390/s120709551 - 12 Jul 2012
Cited by 3 | Viewed by 6508
Abstract
This paper proposes a novel method for identifying carriage errors. A general mathematical model of a guideway system is developed, based on the multi-body system method. Based on the proposed model, most error sources in the guideway system can be measured. The flatness [...] Read more.
This paper proposes a novel method for identifying carriage errors. A general mathematical model of a guideway system is developed, based on the multi-body system method. Based on the proposed model, most error sources in the guideway system can be measured. The flatness of a workpiece measured by the PGI1240 profilometer is represented by a wavelet. Cross-correlation analysis performed to identify the error source of the carriage. The error model is developed based on experimental results on the low frequency components of the signals. With the use of wavelets, the identification precision of test signals is very high. Full article
(This article belongs to the Section Physical Sensors)
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<p>The researched machine tool. (<b>a</b>) The structure; (<b>b</b>) The topology.</p> Full article ">
<p>The processing error caused by the straightness error of carriage.</p> Full article ">
<p>Experimental setup for measurement straightness of cross guideway.</p> Full article ">
<p>Measurement and fitting curve of straightness.</p> Full article ">
<p>Out-of-flatness of workpiece with different feed rates.</p> Full article ">
<p>Squareness of guideway.</p> Full article ">
<p>Decomposed result of test by wavelet transformation.</p> Full article ">
<p>Cross-correlation analysis before using wavelet transformation.</p> Full article ">
<p>Cross-correlation analysis after using wavelet transformation.</p> Full article ">
1044 KiB  
Review
Synthetic Biomimetic Membranes and Their Sensor Applications
by Young-Rok Kim, Sungho Jung, Hyunil Ryu, Yeong-Eun Yoo, Sun Min Kim and Tae-Joon Jeon
Sensors 2012, 12(7), 9530-9550; https://doi.org/10.3390/s120709530 - 11 Jul 2012
Cited by 70 | Viewed by 15084
Abstract
Synthetic biomimetic membranes provide biological environments to membrane proteins. By exploiting the central roles of biological membranes, it is possible to devise biosensors, drug delivery systems, and nanocontainers using a biomimetic membrane system integrated with functional proteins. Biomimetic membranes can be created with [...] Read more.
Synthetic biomimetic membranes provide biological environments to membrane proteins. By exploiting the central roles of biological membranes, it is possible to devise biosensors, drug delivery systems, and nanocontainers using a biomimetic membrane system integrated with functional proteins. Biomimetic membranes can be created with synthetic lipids or block copolymers. These amphiphilic lipids and polymers self-assemble in an aqueous solution either into planar membranes or into vesicles. Using various techniques developed to date, both planar membranes and vesicles can provide versatile and robust platforms for a number of applications. In particular, biomimetic membranes with modified lipids or functional proteins are promising platforms for biosensors. We review recent technologies used to create synthetic biomimetic membranes and their engineered sensors applications. Full article
(This article belongs to the Special Issue Biochips)
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<p>When a hydrogel crosslinks with the head group of a modified lipid, the bilayer is covalently linked to the surrounding hydrogel matrix (right) [<a href="#b29-sensors-12-09530" class="html-bibr">29</a>].</p> Full article ">
<p>Electron micrograph of didodecyldimethylammonium bromide vesicles. (240,000 X). The sample solution was sonicated in the presence of uranyl acetate. Reprinted with permission from Kunitak <span class="html-italic">et al.</span> © 2000 American Chemical Society [<a href="#b31-sensors-12-09530" class="html-bibr">31</a>].</p> Full article ">
<p>Schematic representation of a DNA-loaded ABA copolymer vesicle. <span class="html-italic">λ</span> phage binds to a LamB protein, and the DNA is transferred across the block copolymer membrane. Reprinted with permission from Graff <span class="html-italic">et al.</span> Copyright (2002) PNAS [<a href="#b32-sensors-12-09530" class="html-bibr">32</a>].</p> Full article ">
<p>The triblock copolymer PMOXA-PDMS-PMOXA. The central siloxane region mimics the hydrophobic center in lipid membranes while the hydrophilic PMOXA end blocks mimic polar lipid head groups.</p> Full article ">
<p>Schematic representation of a planar polymer membrane made from tri-block copolymers: PMOXA (poly methyloxazoline)-PDMS (poly dimethylsiloxane)-PMOXA (poly methyloxazoline). Reprinted with permission from Nardin <span class="html-italic">et al.</span> © 2000 American Chemical Society [<a href="#b44-sensors-12-09530" class="html-bibr">44</a>].</p> Full article ">
<p>pH responsive polypeptide vesicles. Schematic illustration of a polypeptide, K<sup>P</sup><sub>160</sub>(L0.3/K0.7)40, and its assembly to a vesicle. Due to the conformational change with pH, molecules entrapped in the vesicle are released. Reprinted by permission from Macmillan Publishers Ltd: Nature Materials [<a href="#b49-sensors-12-09530" class="html-bibr">49</a>], copyright 2004.</p> Full article ">
<p>(<b>a</b>) Two-site sandwich assay. Immobilized ion channels (GT), synthetic archaebacterial membrane-spanning lipids (MSL) and half-membrane-spanning tethered lipids (DLP) are attached to a gold surface. In addition, the membrane is composed of mobile half-membrane-spanning lipids (DPEPC/GDPE) and mobile ion channels (G). The mobile ion channels are coupled to biotinylated antibody fragments (Fab') using streptavidin (SA). When the target analyte is approached to the bilayer, the gramicidin A dimer is displaced upon the binding of the analyte to the binding sites of the lipid surface and of gramicidin, decreasing impedance across the bilayer. (<b>b</b>) Competitive assay. The membrane contains hapten-linked gramicidin, (Gh). When the addition of analyte competes with the happen for Fab', hapten-linked gramicidin will be liberated and associated with another gramicidin, increasing impedance across the bilayer. Reprinted by permission from Macmillan Publishers Ltd: Nature [<a href="#b54-sensors-12-09530" class="html-bibr">54</a>], copyright 1997.</p> Full article ">
<p>(<b>a</b>) Schematic illustration of an electrofluidic lipid membrane biosensor. Red insets are microscope images of the SLB. (<b>b</b>) Left: microscope image of multiple corrals patterned on a glass substrate. Right: electrophoresis of multiple SLB patterns. Reprinted with permission from Lee <span class="html-italic">et al.</span> Copyright (2012) John Wiley &amp; Sons, Inc. [<a href="#b58-sensors-12-09530" class="html-bibr">58</a>].</p> Full article ">
<p>Schematic illustration of SPR and a typical sensorgram. A sensor chip measures the intensity of the reflection of the incident light due to the interaction between the target molecules (green spheres) in the flow solution and the probe molecules (pink diamonds).</p> Full article ">
501 KiB  
Review
Screening of Aptamers on Microfluidic Systems for Clinical Applications
by Chen-Hsun Weng, Chao-Jyun Huang and Gwo-Bin Lee
Sensors 2012, 12(7), 9514-9529; https://doi.org/10.3390/s120709514 - 11 Jul 2012
Cited by 59 | Viewed by 12172
Abstract
The use of microfluidic systems for screening of aptamers and their biomedical applications are reviewed in this paper. Aptamers with different nucleic acid sequences have been extensively studied and the results demonstrated a strong binding affinity to target molecules such that they can [...] Read more.
The use of microfluidic systems for screening of aptamers and their biomedical applications are reviewed in this paper. Aptamers with different nucleic acid sequences have been extensively studied and the results demonstrated a strong binding affinity to target molecules such that they can be used as promising candidate biomarkers for diagnosis and therapeutics. Recently, the aptamer screening protocol has been conducted with microfluidic-based devices. Furthermore, aptamer affinity screening by a microfluidic-based method has demonstrated remarkable advantages over competing traditional methods. In this paper, we first reviewed microfluidic systems which demonstrated efficient and rapid screening of a specific aptamer. Then, the clinical applications of screened aptamers, also performed by microfluidic systems, are further reviewed. These automated microfluidic systems can provide advantages over their conventional counterparts including more compactness, faster analysis, less sample/reagent consumption and automation. An aptamer-based compact microfluidic system for diagnosis may even lead to a point-of-care device. The use of microfluidic systems for aptamer screening and diagnosis is expected to continue growing in the near future and may make a substantial impact on biomedical applications. Full article
(This article belongs to the Special Issue Micro and Nano Technologies for Point-of-Care Diagnosis)
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<p>Schematic illustration of the SELEX processes in CE-microfluidic chips. A library of ssDNA is incubated with the target molecules. Capillary electrophoresis is used to separate bound sequences. Binding nuclear acids are amplified by PCR and purified giving an enriched ssDNA pool which suitable for further rounds of selection. High-affinity aptamers are typically obtained after two to four rounds of selection.</p> Full article ">
<p>Schematic illustration of the SELEX processes in sol-gel microfluidic chips. A library of ssDNA is incubated with sol-gel arrays of proteins in a microfluidic system for efficient selection of ssDNA aptamers against target molecules. The sol-gel microfluidic chips greatly improved selection efficiency, reducing the number of selection cycles needed to produce high affinity aptamers.</p> Full article ">
<p>Schematic illustration of the SELEX processes in magnetic-bead-based microfluidic chips. The microfluidic selection process begins with the incubation of random ssDNA library with target proteins conjugated to magnetic beads. After incubation, the partitioning step to separate the target-bound aptamers from the unbound nuclear acids is performed in the microfluidic chip. Stringent washing conditions then are imposed in the microchannel to continuously elute weakly- and unbound nuclear acids from the microfluidic chip. After the separation, the external magnets are removed, and the beads carrying the selected aptamers are released from the device. The entire separation process with trapping, washing, and bead elution performs on chip. Finally, the selected aptamers are amplified via PCR.</p> Full article ">
<p>(<b>a</b>) Schematic illustration of the pneumatic micropump/micromixer; (<b>b</b>-I) The working principle of the membrane-type micropump. The forward-motion of the fluids in the microchannel is activated as the compressed air is injected; (<b>b</b>-II) The fluid in the microchannel is driven from the right side to the left side; (<b>c</b>-I) Initial state of the micromixer without a supply of compressed air; (<b>c</b>-II) The mixing state of the micromixer when supplied with compressed air.</p> Full article ">
<p>Schematic illustration of the Cell-SELEX processes in magnetic-bead-based microfluidic chips. Aptamers were bound to the target cells, and control cells were used for negative counter-selection. After 15–20 cycles of positive/negative selection, the highly-specific aptamer for the target cells can be identified.</p> Full article ">
<p>Illustrations of various detection techniques for aptamer-based assays in microfluidic chips including (<b>a</b>) an electrochemical-based detection: a simple and sensitive method has been developed, the microchannel is immobilized aptamer. Then, the target proteins are sequentially captured by the specific aptamer–protein interaction. Finally, an electrochemical system is employed to detect the current response; (<b>b</b>) a fluorescent-based detection method: the sandwich assay, which is one of the most used assay formats. In this approach, the analyte is sandwiched by two specific probes, one capture probe and the other reporter probe. Capture probes as aptamers are often immobilized on microchannels, while reporter probes as antibodies are often conjugated with signaling moieties (e.g., fluorescent, enzymes or nanoparticles (NPs)); (<b>c</b>) a SPR sensing scheme: In this SPR sensing device, a selective surface is formed by immobilizing the aptamer on the surface. Then, the target is injected at a constant flow rate, while the instrument measures changes in the resonance angle that occur at the surface. The angle changes due to aptamer binding to the target. The signal is proportional to the number of bound molecules, thus the SPR method allows for label-free detection in a microfluidic chip with single-site binding resolution.</p> Full article ">
580 KiB  
Article
Monitoring of Temperature Fatigue Failure Mechanism for Polyvinyl Alcohol Fiber Concrete Using Acoustic Emission Sensors
by Dongsheng Li and Hai Cao
Sensors 2012, 12(7), 9502-9513; https://doi.org/10.3390/s120709502 - 11 Jul 2012
Cited by 7 | Viewed by 6567
Abstract
The applicability of acoustic emission (AE) techniques to monitor the mechanism of evolution of polyvinyl alcohol (PVA) fiber concrete damage under temperature fatigue loading is investigated. Using the temperature fatigue test, real-time AE monitoring data of PVA fiber concrete is achieved. Based on [...] Read more.
The applicability of acoustic emission (AE) techniques to monitor the mechanism of evolution of polyvinyl alcohol (PVA) fiber concrete damage under temperature fatigue loading is investigated. Using the temperature fatigue test, real-time AE monitoring data of PVA fiber concrete is achieved. Based on the AE signal characteristics of the whole test process and comparison of AE signals of PVA fiber concretes with different fiber contents, the damage evolution process of PVA fiber concrete is analyzed. Finally, a qualitative evaluation of the damage degree is obtained using the kurtosis index and b-value of AE characteristic parameters. The results obtained using both methods are discussed. Full article
(This article belongs to the Section Physical Sensors)
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<p>Temperature loading procedures.</p> Full article ">
<p>PVA concrete temperature fatigue damage testing experimental device.</p> Full article ">
<p>AE sensors arrangement (units: mm).</p> Full article ">
<p>AE cumulative energy <span class="html-italic">vs.</span> time.</p> Full article ">
<p>AE amplitude <span class="html-italic">vs.</span> duration (1.5 kg/m<sup>3</sup>).</p> Full article ">
<p>AE amplitude <span class="html-italic">vs.</span> duration (1.0 kg/m<sup>3</sup>).</p> Full article ">
<p>AE amplitude <span class="html-italic">vs.</span> duration (0.5 kg/m<sup>3</sup>).</p> Full article ">
<p>AE amplitude statistical distributions for PVA fiber contents concrete with: (<b>a</b>) 1.5 kg/m<sup>3</sup>, (<b>b</b>) 1.0 kg/m<sup>3</sup> and (<b>c</b>) 0.5 kg/m<sup>3</sup>.</p> Full article ">
<p>AE amplitude statistical distributions for PVA fiber contents concrete with: (<b>a</b>) 1.5 kg/m<sup>3</sup>, (<b>b</b>) 1.0 kg/m<sup>3</sup> and (<b>c</b>) 0.5 kg/m<sup>3</sup>.</p> Full article ">
<p>Temperature fatigue load and AE amplitude <span class="html-italic">vs.</span> time.</p> Full article ">
400 KiB  
Article
A Bayesian Framework for the Automated Online Assessment of Sensor Data Quality
by Daniel Smith, Greg Timms, Paulo De Souza and Claire D’Este
Sensors 2012, 12(7), 9476-9501; https://doi.org/10.3390/s120709476 - 11 Jul 2012
Cited by 24 | Viewed by 8165
Abstract
Online automated quality assessment is critical to determine a sensor’s fitness for purpose in real-time applications. A Dynamic Bayesian Network (DBN) framework is proposed to produce probabilistic quality assessments and represent the uncertainty of sequentially correlated sensor readings. This is a novel framework [...] Read more.
Online automated quality assessment is critical to determine a sensor’s fitness for purpose in real-time applications. A Dynamic Bayesian Network (DBN) framework is proposed to produce probabilistic quality assessments and represent the uncertainty of sequentially correlated sensor readings. This is a novel framework to represent the causes, quality state and observed effects of individual sensor errors without imposing any constraints upon the physical deployment or measured phenomenon. It represents the casual relationship between quality tests and combines them in a way to generate uncertainty estimates of samples. The DBN was implemented for a particular marine deployment of temperature and conductivity sensors in Hobart, Australia. The DBN was shown to offer a substantial average improvement (34%) in replicating the error bars that were generated by experts when compared to a fuzzy logic approach. Full article
(This article belongs to the Section Physical Sensors)
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<p>A Bayesian network is a directed acyclic graph representing the joint probability of a problem. Each node in the network is associated with a conditional probability distribution of a variable that is conditioned upon other variables with edges pointing towards it. This particular network structure is used to assess the data quality of temperature and conductivity sensors deployed in Sullivans Cove, Hobart with cause and observed evidence tests. The causes of sensor degradation include the time since the sensor was calibrated (node <b>A</b>) and the time since the sensor was cleaned (node <b>B</b>). Node <b>C</b> was used to infer the latent quality state. The observed evidence of the data quality was the seasonal difference (node <b>D</b>), the gradient (node <b>E</b>), the difference between the sensor and hydrodynamic model (node <b>F</b>) and the difference between equivalent sensors at alternate depths (node <b>G</b>). The CPD of the network have been trained from observations of a temperature sensor deployed at 1m in Sullivans Cove.</p> Full article ">
<p>The two time-slice structure of the Dynamic Bayesian Network used to perform quality state inference for each incoming sample. The interface algorithm only requires the node variables from the previous slice that are connected to the current slice to be involved in the quality state inference. This is known as the 1.5 DBN structure.</p> Full article ">
<p>The 1.5 DBN model used to assess the data quality of individual temperature and conductivity sensors in Sullivans Cove, Hobart at 1 m and 10 m. The causes of sensor degradation in this model were the time since the sensor was calibrated in node <b>A</b> and the time since the sensor was cleaned in node <b>B</b>. The latent states used to infer the data quality in node <b>C</b> were defined by the IOC flagging standard. The observed evidence of data quality was the seasonal difference in node <b>D</b>, the gradient in node <b>E</b>, the difference between the sensor and hydrodynamic model in node <b>F</b> (only for sensors at 1 m) and in node <b>G</b> the difference between equivalent sensors at alternate depths.</p> Full article ">
<p>The trained CPD of the quality state conditioned upon the time since the conductivity sensor at 1 m was cleaned. The CPD was trained from the data set specified in Section 6.4 and the labels 1–4 correspond to the quality states in <a href="#t1-sensors-12-09476" class="html-table">Table 1</a>.</p> Full article ">
<p>A comparison of the corresponding readings from co-situated conductivity sensors at 1 m (<span class="html-italic">x</span><sub>1</sub>(<span class="html-italic">t</span>)) and 10 m (<span class="html-italic">x</span><sub>2</sub>(<span class="html-italic">t</span>)). (i) The sensor <span class="html-italic">x</span><sub>1</sub>(<span class="html-italic">t</span>) had a step change in its readings as a result of an electronic fault; (ii) The difference test (<span class="html-italic">x<sub>sr</sub></span>(<span class="html-italic">t</span>)) between the sensors could identify the fault but can not resolve which of the sensors was responsible. The <span class="html-italic">x<sub>sr</sub></span>(<span class="html-italic">t</span>) test was conditioned upon the gradient test <span class="html-italic">x<sub>gr</sub></span>(<span class="html-italic">t</span>) shown in (iii) and previous class state <span class="html-italic">q<sub>t</sub></span><sub>−1</sub> to infer <span class="html-italic">x</span><sub>1</sub>(<span class="html-italic">t</span>) was erroneous.</p> Full article ">
<p>The automated quality assessments from two BN (static BN and DBN) compared to expert quality assessments across the four sensors in Sullivans Cove, Hobart. The quality state labels 1 to 4 define the quality states in <a href="#t1-sensors-12-09476" class="html-table">Table 1</a>. There were two metrics used to compare the assessment performance of the Bayesian networks. The first metric was the distance between the quality state with maximum posterior probability and the quality state selected by an expert. The second metric was the distance between the expert's quality state and the continuous quality label of the network defined in <a href="#FD11" class="html-disp-formula">Equation (11)</a>. (<b>a</b>) Temperature Sensor at 1 m; (<b>b</b>) Conductivity Sensor at 1 m; (<b>c</b>) Temperature Sensor at 10 m; (<b>d</b>) Conductivity Sensor at 10 m.</p> Full article ">
<p>The top time-series of each figure corresponds to a section of sensor readings from the conductivity sensor at 1 m that have been assessed by a human expert and automatically flagged by the DBN. The four bottom series correspond to the posterior probabilities of the (between 0–1) quality states of each sensor sample in the network. The arrows upon the top time-series correspond to the points at which the expert's assessment has changed to the quality state specified.</p> Full article ">
<p>The top time-series of each figure corresponds to a section of sensor readings from the conductivity sensor at 1 m that have been assessed by a human expert and automatically flagged by the static BN. The four bottom series correspond to the posterior probabilities of the (between 0–1) quality states of each sensor sample in the network. The arrows upon the top time-series correspond to the points at which the expert's assessment has changed to the quality state specified.</p> Full article ">
312 KiB  
Article
A Portable and Power-Free Microfluidic Device for Rapid and Sensitive Lead (Pb2+) Detection
by Chunhui Fan, Shijiang He, Gang Liu, Lianhui Wang and Shiping Song
Sensors 2012, 12(7), 9467-9475; https://doi.org/10.3390/s120709467 - 10 Jul 2012
Cited by 44 | Viewed by 8882
Abstract
A portable and power-free microfluidic device was designed for rapid and sensitive detection of lead (Pb2+). 11-mercaptoundecanoic acid (MUA)-functionalized gold nanoparticles (MUA-AuNPs) aggregated in the presence of Pb2+ for the chelation mechanism. When we performed this analysis on a polydimethylsiloxane [...] Read more.
A portable and power-free microfluidic device was designed for rapid and sensitive detection of lead (Pb2+). 11-mercaptoundecanoic acid (MUA)-functionalized gold nanoparticles (MUA-AuNPs) aggregated in the presence of Pb2+ for the chelation mechanism. When we performed this analysis on a polydimethylsiloxane (PDMS) microfluidic chip, the aggregations deposited onto the surface of chip and formed dark lines along the laminar flows in the zigzag microchannels. This visual result can be observed by the naked eye through a microscope or just a drop of water as a magnifier. Ten μM Pb2+ was successfully detected. Full article
(This article belongs to the Section Biosensors)
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<p>Schematic illustration of the chelation mechanism of Pb<sup>2+</sup> ions and MUA-AuNPs.</p> Full article ">
<p>11-Mercaptoundecanoic acid (MUA) molecule (C<sub>11</sub>H<sub>22</sub>O<sub>2</sub>S).</p> Full article ">
<p>Photographic image of MUA-AuNPs, with their colour visibly changed in the presence of Pb<sup>2+</sup>. (1) Deionized water; (2) 0.05 mM Pb<sup>2+</sup>; (3) 0.025 mM Pb<sup>2+</sup>; (4) 0.01 mM Pb<sup>2+</sup>; (5) 0.005 mM Pb<sup>2+</sup>.</p> Full article ">
<p>Microscope images of the analysis results for different concentration of Pb<sup>2+</sup>: (A) Deionized water; (B) 10 μM Pb<sup>2+</sup>; (C) 25 μM Pb<sup>2+</sup>; (D) 50 μM Pb<sup>2+</sup>;(E) 100 μM Pb<sup>2+</sup>.</p> Full article ">
<p>Microscope images of the lines in multi-microchannels microfluidic chip in the presence of different ion solutions. (1) 100 μM Mg<sup>2+</sup>; (2) 100 μM Ca<sup>2+</sup>; (3) 100 μM NaCl; (4) Deionized water; (5) 10 μM Pb<sup>2+</sup>; (6) 25 μM Pb<sup>2+</sup>; (7) 50 μM Pb<sup>2+</sup>; (8) 100 μM Pb<sup>2+</sup>.</p> Full article ">
<p>Image taken by a camera through a drop of water on a microfluidic chip. Channel 1–8 showed the analysis result from samples of different concentrations of various ions corresponding to the results shown in <a href="#f4-sensors-12-09467" class="html-fig">Figure 4</a>: (1) Deionized water; (2) 0.1 mM NaCl; (3) 0.1 mM Ca<sup>2+</sup>; (4) 0.1 mM Mg<sup>2+</sup>; (5) 0.1 mM Pb<sup>2+</sup>; (6) 0.05 mM Pb<sup>2+</sup>; (7) 25 μM Pb<sup>2+</sup>; (8) 10 μM Pb<sup>2+</sup>.</p> Full article ">
642 KiB  
Article
An Enhanced MEMS Error Modeling Approach Based on Nu-Support Vector Regression
by Deepak Bhatt, Priyanka Aggarwal, Prabir Bhattacharya and Vijay Devabhaktuni
Sensors 2012, 12(7), 9448-9466; https://doi.org/10.3390/s120709448 - 9 Jul 2012
Cited by 55 | Viewed by 9328
Abstract
Micro Electro Mechanical System (MEMS)-based inertial sensors have made possible the development of a civilian land vehicle navigation system by offering a low-cost solution. However, the accurate modeling of the MEMS sensor errors is one of the most challenging tasks in the design [...] Read more.
Micro Electro Mechanical System (MEMS)-based inertial sensors have made possible the development of a civilian land vehicle navigation system by offering a low-cost solution. However, the accurate modeling of the MEMS sensor errors is one of the most challenging tasks in the design of low-cost navigation systems. These sensors exhibit significant errors like biases, drift, noises; which are negligible for higher grade units. Different conventional techniques utilizing the Gauss Markov model and neural network method have been previously utilized to model the errors. However, Gauss Markov model works unsatisfactorily in the case of MEMS units due to the presence of high inherent sensor errors. On the other hand, modeling the random drift utilizing Neural Network (NN) is time consuming, thereby affecting its real-time implementation. We overcome these existing drawbacks by developing an enhanced Support Vector Machine (SVM) based error model. Unlike NN, SVMs do not suffer from local minimisation or over-fitting problems and delivers a reliable global solution. Experimental results proved that the proposed SVM approach reduced the noise standard deviation by 10–35% for gyroscopes and 61–76% for accelerometers. Further, positional error drifts under static conditions improved by 41% and 80% in comparison to NN and GM approaches. Full article
(This article belongs to the Section Physical Sensors)
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<p>Gyroscope turn-on to turn-on biases.</p> Full article ">
<p>Gyroscope in-run biases (const. temp.).</p> Full article ">
<p>Gyroscope in-run biases (vary temp.)</p> Full article ">
<p>Allan variance for gyroscopes.</p> Full article ">
<p>Allan variance for accelerometers.</p> Full article ">
<p>Autocorrelation sequence: (<b>a</b>) gyroscope; (<b>b</b>) accelerometer.</p> Full article ">
<p>Gyroscope X output, red: uncompensated, blue: compensated.</p> Full article ">
<p>Gyroscope X output, red: uncompensated; blue: compensated using Nu-SVR approach.</p> Full article ">
<p>Position drifts by GM, RBFNN and Nu-SVR methods.</p> Full article ">
4047 KiB  
Article
A Fully Sensorized Cooperative Robotic System for Surgical Interventions
by Saúl Tovar-Arriaga, José Emilio Vargas, Juan M. Ramos, Marco A. Aceves, Efren Gorrostieta and Willi A. Kalender
Sensors 2012, 12(7), 9423-9447; https://doi.org/10.3390/s120709423 - 9 Jul 2012
Cited by 12 | Viewed by 12906
Abstract
In this research a fully sensorized cooperative robot system for manipulation of needles is presented. The setup consists of a DLR/KUKA Light Weight Robot III especially designed for safe human/robot interaction, a FD-CT robot-driven angiographic C-arm system, and a navigation camera. Also, new [...] Read more.
In this research a fully sensorized cooperative robot system for manipulation of needles is presented. The setup consists of a DLR/KUKA Light Weight Robot III especially designed for safe human/robot interaction, a FD-CT robot-driven angiographic C-arm system, and a navigation camera. Also, new control strategies for robot manipulation in the clinical environment are introduced. A method for fast calibration of the involved components and the preliminary accuracy tests of the whole possible errors chain are presented. Calibration of the robot with the navigation system has a residual error of 0.81 mm (rms) with a standard deviation of ±0.41 mm. The accuracy of the robotic system while targeting fixed points at different positions within the workspace is of 1.2 mm (rms) with a standard deviation of ±0.4 mm. After calibration, and due to close loop control, the absolute positioning accuracy was reduced to the navigation camera accuracy which is of 0.35 mm (rms). The implemented control allows the robot to compensate for small patient movements. Full article
(This article belongs to the Section Physical Sensors)
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<p>Sketch of a fully integrated system for percutaneous procedures.</p> Full article ">
<p>System setup in the interventional suite.</p> Full article ">
<p>Mobile robot platform with mounted DLR/KUKA Light Weight Robot III. (<b>a</b>) The real-time robot controller, the application controller, a DeviceNET bus terminal and a touch screen are integrated; (<b>b</b>) Platform with covers attached to it.</p> Full article ">
<p>(<b>a</b>) robot handle together with the needle holder. A DRF is attached to the tool in order to be tracked by the navigation system; (<b>b</b>) the tool was designed autoclavable. The beige color parts are made of PEEK to ensure artifact-free imaging.</p> Full article ">
<p>Control architecture. The application controller receives information from the different components of the system and uses it to control the robot arm.</p> Full article ">
<p>During initialization, all the channels necessary to make the application controller communicate with the main components of the system are opened. Then, the application controller and the KRC interchange information via RSI in order to control the robot motion.</p> Full article ">
<p>Control loop to manipulate the robot pose in the application controller.</p> Full article ">
<p>DeviceNet link. The data in the bus can be written/read by any of the connected cards.</p> Full article ">
<p>Inner connections of the robotic system, including a DeviceNet bus terminal and power supply.</p> Full article ">
710 KiB  
Article
Dynamics of Ras Complexes Observed in Living Cells
by Xiangyong Li, Zhiyong Cheng and Honglin Jin
Sensors 2012, 12(7), 9411-9422; https://doi.org/10.3390/s120709411 - 9 Jul 2012
Cited by 4 | Viewed by 7527
Abstract
K-Ras works as a switch in many important intracellular signaling pathways and plays important roles in cell growth, proliferation, differentiation and carcinogenesis. For signal transduction from K-Ras to Raf1, the best-characterized effector of K-Ras, the general view is that Ras recruits Raf1 from [...] Read more.
K-Ras works as a switch in many important intracellular signaling pathways and plays important roles in cell growth, proliferation, differentiation and carcinogenesis. For signal transduction from K-Ras to Raf1, the best-characterized effector of K-Ras, the general view is that Ras recruits Raf1 from the cytoplasm to the cell membrane. To elucidate this process, we constructed a series of fusion proteins (including Raf1 and K-Ras fused with either fluorescent proteins or fluorescent protein fragments) to compare subcellular localizations of these proteins. Bimolecular fluorescence complementation (BiFC) and a co-transfection system were used. In the BiFC system, the K-Ras/Raf1 complexes were mainly located in the cell membrane, while the Raf1 control was uniformly distributed in the cytoplasm. However, the complexes of Raf1 and K-RasC185S, a K-Ras mutant which loses membrane-localization, were also able to accumulate in the cell membrane. In contrast, an apparent cytosolic distribution pattern was observed in cells co-transfected with mcerulean-Raf1 and EGFP-K-RasC185S, suggesting that the membrane localization of K-Ras/Raf1 complexes is not entirely dependent on K-Ras, and that other factors, such as the irreversible conformation formed between K-Ras and Raf1 may play a role. This study sheds light on the interaction between K-Ras and Raf1 and provides a practical method to elucidate the mechanism underlying K-Ras and Raf1 binding to the cell membrane. Full article
(This article belongs to the Special Issue Live Cell-Based Sensors)
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<p>Principle of BiFC for K-Ras-Raf1. (<b>A</b>) View of BiFC principle. N- and C-terminal fragments of fluorescent proteins Venus were fused to N-termindal of Raf1 and K-Ras, respectively. The interaction between Raf1 and K-Ras brings N- and C-terminal fragments in proximity to reconstitute an intact Venus. (<b>B</b>) Schematic representation of the plasmid constructs made and used in this study.</p> Full article ">
<p>Kinetics of K-Ras/Raf1 interaction. (<b>A</b>) Serum starved COS-7 cells were transfected with VN-Raf1-VC-K-Ras, and 16 h later were treated with 100 ng/mL EGF. Time interval between adjacent two images is 2 minutes. (<b>B</b>) BiFC vectors were co-transfected with mCerulean-C1. Fluorescent intensity was represented by ratio of yellow and cyan fluorescence. Mean fluorescent intensity of RBD/K-Ras, RBD/H-Ras, Raf1/K-Ras and Raf1/K-RasC185S were monitored upon EGF stimulation. (<b>C</b>) Confocal images of cells co-transfected with pBud-Vn-Raf1-Vc-K-Ras (K-Ras 12v or K-Ras C185S) and pmCerulean-C1. (<b>D</b>) Mean fluorescent intensity of R-K (cells expressed VN-Raf1-VC-K-Ras), R-K+EGF (EGF stimulated cells expressed VN-Raf1-VC-K-Ras for 5 h) and R-KCS (cells expressed VN-Raf1-VC-K-RasC185S). In each experiment (n = 3), 50 individual cells in each group were measured. Significant differences in fluorescence ratio (* <span class="html-italic">P</span> &lt; 0.05 and *** <span class="html-italic">P</span> &lt; 0.001) were observed between groups as indicated. Scale bar, 10 μm.</p> Full article ">
<p>Sub-localization of Raf1/K-Ras complexes and Raf1/K-Ras-C185S in BiFC assays. (<b>A</b>) COS-7 cells expressing VN-Raf1/VC-K-Ras were observed with confocal microscopy, and the xy, xz, and yz images are shown, respectively. (<b>B</b>) COS-7 cells were transfected with expression vectors for VN-Raf1-VC-K-Ras C185S. Scale bar, 10 μm.</p> Full article ">
<p>Sub-cellular localization of K-Ras, K-Ras-C185S and Raf1 in COS-7 cells. (<b>A</b>) Expression of mCerulean-Raf1, EGFP-K-Ras, and EGFP-K-Ras-C185S in COS-7 cells, respectively. (<b>B</b>) Co-expression of EGFP-K-Ras and mCerulean-Raf1 in COS-7 cells, and co-localization of the two proteins was clearly observed at the cell membrane. (<b>C</b>) Co-expression of EGFP-K-Ras-C185S and mCerulean-Raf1 in COS-7 cells. The mean colocalization Pearson′s Rr of Raf1-Kras and Raf1-K-RasC185S are listed in (B) and (C). Colocalization analysis was performed using the Image J software. Scale bar, 10 μm.</p> Full article ">
2047 KiB  
Article
AUV SLAM and Experiments Using a Mechanical Scanning Forward-Looking Sonar
by Bo He, Yan Liang, Xiao Feng, Rui Nian, Tianhong Yan, Minghui Li and Shujing Zhang
Sensors 2012, 12(7), 9386-9410; https://doi.org/10.3390/s120709386 - 9 Jul 2012
Cited by 53 | Viewed by 11067
Abstract
Navigation technology is one of the most important challenges in the applications of autonomous underwater vehicles (AUVs) which navigate in the complex undersea environment. The ability of localizing a robot and accurately mapping its surroundings simultaneously, namely the simultaneous localization and mapping (SLAM) [...] Read more.
Navigation technology is one of the most important challenges in the applications of autonomous underwater vehicles (AUVs) which navigate in the complex undersea environment. The ability of localizing a robot and accurately mapping its surroundings simultaneously, namely the simultaneous localization and mapping (SLAM) problem, is a key prerequisite of truly autonomous robots. In this paper, a modified-FastSLAM algorithm is proposed and used in the navigation for our C-Ranger research platform, an open-frame AUV. A mechanical scanning imaging sonar is chosen as the active sensor for the AUV. The modified-FastSLAM implements the update relying on the on-board sensors of C-Ranger. On the other hand, the algorithm employs the data association which combines the single particle maximum likelihood method with modified negative evidence method, and uses the rank-based resampling to overcome the particle depletion problem. In order to verify the feasibility of the proposed methods, both simulation experiments and sea trials for C-Ranger are conducted. The experimental results show the modified-FastSLAM employed for the navigation of the C-Ranger AUV is much more effective and accurate compared with the traditional methods. Full article
(This article belongs to the Special Issue New Trends towards Automatic Vehicle Control and Perception Systems)
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<p>. (<b>a</b>) C-Ranger in deployment; (<b>b</b>) The coordinate system of the C-Ranger platform.</p> Full article ">
<p>Control architecture of the C-Ranger.</p> Full article ">
<p>Effect of the vehicle motion on acoustic images. (<b>a</b>) Raw sonar image; (<b>b</b>) Corrected sonar image; (c) Zenithal view of the Abandoned Marina.</p> Full article ">
<p>Results of FastSLAM and modified-FastSLAM obtained by averaging over 50 Monte-Carlo trials.</p> Full article ">
<p>Data association results.</p> Full article ">
<p>Number of distinct particles over time. The particle number used is 50.</p> Full article ">
<p>Estimation pose error with 2-σ uncertainty bound of the original FastSLAM and the modified FastSLAM algorithm.</p> Full article ">
<p>RMS error of the two algorithms.</p> Full article ">
<p>Average NEES of the two algorithms.</p> Full article ">
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