A reusable smart interface for gas sensor resistance measurement

The advances of the semiconductor industry enable microelectromechanical systems sensors, signal conditioning logic and network access to be integrated into a smart sensor node. In this framework, a mixed-mode interface circuit for monolithically integrated gas sensor arrays was developed with high-level design techniques. This interface system includes analog electronics for inspection of up to four sensor arrays and digital logic for smart control and data communication. Although different design methodologies were used in the conception of the complete circuit, high-level synthesis tools and methodologies were crucial in speeding up the whole design cycle, enhancing reusability for future applications and producing a flexible and robust component.

On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.

A current-mode interface circuit for a piezoresistive pressure sensor

An interfacing circuit for piezoresistive pressure sensors based on CMOS current conveyors is presented. The main advantages of the proposed interfacing circuit include the use of a single piezoresistor, the capability of offset compensation, and a versatile current-mode configuration, with current output and current or voltage input. Experimental tests confirm linear relation of output voltage versus piezoresistance variation.

The unfolded protein response: integrating stress signals through the stress sensor IRE1α.

Stress induced by accumulation of unfolded proteins at the endoplasmic reticulum (ER) is a classic feature of secretory cells and is observed in many tissues in human diseases including cancer, diabetes, obesity, and neurodegeneration. Cellular adaptation to ER stress is achieved by the activation of the unfolded protein response (UPR), an integrated signal transduction pathway that transmits information about the protein folding status at the ER to the nucleus and cytosol to restore ER homeostasis. Inositol-requiring transmembrane kinase/endonuclease-1 (IRE1α), the most conserved UPR stress sensor, functions as an endoribonuclease that processes the mRNA of the transcription factor X-box binding protein-1 (XBP1). IRE1α signaling is a highly regulated process, controlled by the formation of a dynamic scaffold onto which many regulatory components assemble, here referred to as the UPRosome. Here we provide an overview of the signaling and regulatory mechanisms underlying IRE1α function and discuss the emerging role of the UPR in adaptation to protein folding stress in specialized secretory cells and in pathological conditions associated with alterations in ER homeostasis.

Gas identification with tin oxide sensor array and self-organizing maps: adaptive correction of sensor drifts

Low-cost tin oxide gas sensors are inherently nonspecific. In addition, they have several undesirable characteristics such as slow response, nonlinearities, and long-term drifts. This paper shows that the combination of a gas-sensor array together with self-organizing maps (SOM's) permit success in gas classification problems. The system is able to determine the gas present in an atmosphere with error rates lower than 3%. Correction of the sensor's drift with an adaptive SOM has also been investigated

Drift compensation of gas sensor array data by Orthogonal Signal Correction

Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

Drift compensation of gas sensor array data by common principal component analysis

A new drift compensation method based on Common Principal Component Analysis (CPCA) is proposed. The drift variance in data is found as the principal components computed by CPCA. This method finds components that are common for all gasses in feature space. The method is compared in classification task with respect to the other approaches published where the drift direction is estimated through a Principal Component Analysis (PCA) of a reference gas. The proposed new method ¿ employing no specific reference gas, but information from all gases ¿has shown the same performance as the traditional approach with the best-fitted reference gas. Results are shown with data lasting 7-months including three gases at different concentrations for an array of 17 polymeric sensors.

Electrochemical As(III) whole-cell based biochip sensor.

The development of a whole-cell based sensor for arsenite detection coupling biological engineering and electrochemical techniques is presented. This strategy takes advantage of the natural Escherichia coli resistance mechanism against toxic arsenic species, such as arsenite, which consists of the selective intracellular recognition of arsenite and its pumping out from the cell. A whole-cell based biosensor can be produced by coupling the intracellular recognition of arsenite to the generation of an electrochemical signal. Hereto, E. coli was equipped with a genetic circuit in which synthesis of beta-galactosidase is under control of the arsenite-derepressable arsR-promoter. The E. coli reporter strain was filled in a microchip containing 16 independent electrochemical cells (i.e. two-electrode cell), which was then employed for analysis of tap and groundwater samples. The developed arsenic-sensitive electrochemical biochip is easy to use and outperforms state-of-the-art bacterial bioreporters assays specifically in its simplicity and response time, while keeping a very good limit of detection in tap water, i.e. 0.8ppb. Additionally, a very good linear response in the ranges of concentration tested (0.94ppb to 3.75ppb, R(2)=0.9975 and 3.75 ppb to 30ppb, R(2)=0.9991) was obtained, complying perfectly with the acceptable arsenic concentration limits defined by the World Health Organization for drinking water samples (i.e. 10ppb). Therefore, the proposed assay provides a very good alternative for the portable quantification of As (III) in water as corroborated by the analysis of natural groundwater samples from Swiss mountains, which showed a very good agreement with the results obtained by atomic absorption spectroscopy.

Optical crop sensor for variable-rate nitrogen fertilization in corn: i - plant nutrition and dry matter production

Variable-rate nitrogen fertilization (VRF) based on optical spectrometry sensors of crops is a technological innovation capable of improving the nutrient use efficiency (NUE) and mitigate environmental impacts. However, studies addressing fertilization based on crop sensors are still scarce in Brazilian agriculture. This study aims to evaluate the efficiency of an optical crop sensor to assess the nutritional status of corn and compare VRF with the standard strategy of traditional single-rate N fertilization (TSF) used by farmers. With this purpose, three experiments were conducted at different locations in Southern Brazil, in the growing seasons 2008/09 and 2010/11. The following crop properties were evaluated: above-ground dry matter production, nitrogen (N) content, N uptake, relative chlorophyll content (SPAD) reading, and a vegetation index measured by the optical sensor N-Sensor® ALS. The plants were evaluated in the stages V4, V6, V8, V10, V12 and at corn flowering. The experiments had a completely randomized design at three different sites that were analyzed separately. The vegetation index was directly related to above-ground dry matter production (R² = 0.91; p<0.0001), total N uptake (R² = 0.87; p<0.0001) and SPAD reading (R² = 0.63; p<0.0001) and inversely related to plant N content (R² = 0.53; p<0.0001). The efficiency of VRF for plant nutrition was influenced by the specific climatic conditions of each site. Therefore, the efficiency of the VRF strategy was similar to that of the standard farmer fertilizer strategy at sites 1 and 2. However, at site 3 where the climatic conditions were favorable for corn growth, the use of optical sensors to determine VRF resulted in a 12 % increase in N plant uptake in relation to the standard fertilization, indicating the potential of this technology to improve NUE.

Optical crop sensor for variable-rate nitrogen fertilization in corn: II - indices of fertilizer efficiency and corn yield

Generally, in tropical and subtropical agroecosystems, the efficiency of nitrogen (N) fertilization is low, inducing a temporal variability of crop yield, economic losses, and environmental impacts. Variable-rate N fertilization (VRF), based on optical spectrometry crop sensors, could increase the N use efficiency (NUE). The objective of this study was to evaluate the corn grain yield and N fertilization efficiency under VRF determined by an optical sensor in comparison to the traditional single-application N fertilization (TSF). With this purpose, three experiments with no-tillage corn were carried out in the 2008/09 and 2010/11 growing seasons on a Hapludox in South Brazil, in a completely randomized design, at three different sites that were analyzed separately. The following crop properties were evaluated: aboveground dry matter production and quantity of N uptake at corn flowering, grain yield, and vegetation index determined by an N-Sensor® ALS optical sensor. Across the sites, the corn N fertilizer had a positive effect on corn N uptake, resulting in increased corn dry matter and grain yield. However, N fertilization induced lower increases of corn grain yield at site 2, where there was a severe drought during the growing period. The VRF defined by the optical crop sensor increased the apparent N recovery (NRE) and agronomic efficiency of N (NAE) compared to the traditional fertilizer strategy. In the average of sites 1 and 3, which were not affected by drought, VRF promoted an increase of 28.0 and 41.3 % in NAE and NRE, respectively. Despite these results, no increases in corn grain yield were observed by the use of VRF compared to TSF.

Correction of aberration in holographic optical tweezers using a Shack-Hartmann sensor

Optical aberration due to the nonflatness of spatial light modulators used in holographic optical tweezers significantly deteriorates the quality of the trap and may easily prevent stable trapping of particles. We use a Shack-Hartmann sensor to measure the distorted wavefront at the modulator plane; the conjugate of this wavefront is then added to the holograms written into the display to counteract its own curvature and thus compensate the optical aberration of the system. For a Holoeye LC-R 2500 reflective device, flatness is improved from 0.8¿ to ¿/16 (¿=532 nm), leading to a diffraction-limited spot at the focal plane of the microscope objective, which makes stable trapping possible. This process could be fully automated in a closed-loop configuration and would eventually allow other sources of aberration in the optical setup to be corrected for.

Risk evaluation for spoofing against a sensor supplied with liveness detection

The aim of this paper is to evaluate the risks associated with the use of fake fingerprints on a livescan supplied with a method of liveness detection. The method is based on optical properties of the skin. The sensor uses several polarizations and illuminations to capture the information of the different layers of the human skin. These experiments also allow for the determination under which conditions the system is deceived and if there is an influence respectively of the nature of the fake, the mould used for the production or the individuals involved in the attack. These experiments showed that current multispectral sensors can be deceived by the use of fake fingerprints created with or without the cooperation of the subject. Fakes created from direct casts perform better than those produced by fakes created from indirect casts. The results showed that the success of the attack is influenced by two main factors. The first is the quality of the fakes, and by extension the quality of the original fingerprint. The second is the combination of the general patterns involved in the attacks since an appropriate combination can strongly increase the rates of successful attacks.

The endoplasmic reticulum: a sensor of cellular stress that modulates immune responses.

Many inflammatory and infectious diseases are characterized by the activation of signaling pathways steaming from the endoplasmic reticulum (ER). These pathways, primarily associated with loss of ER homeostasis, are emerging as key regulators of inflammation and infection. Recent advances shed light on the mechanisms linking ER-stress and immune responses.