Twin-Grating Fiber Optic Sensors Applied on Wavelength- Division Multiplexing and Its Numerical Resolution

In this work, the twin-grating fiber optic sensor has been applied on wavelength-division multiplexing. A quasi-distributed sensor formed by three local twin-grating sensors, is numerically simulated. The wavelength channels were 1531.5, 1535.5, and 1539.5 nm. The numerical simulation shows the resolution vs. signal-to-noise rate. Three local twin-grating sensors have approximately the same resolution because all local sensors have the same cavity length and the wavelength channels are very close. All local sensors have two numerical resolutions because the Fourier domain phase analysis algorithm makes two evaluations of the Bragg wavelength shift. The transition between both resolutions can be calculated with the parameters: cavity length, Bragg wavelength channel, refraction index, and enveloped resolution. This transition depends on the noise system, demodulation algorithm, instrumentation, and local sensor properties. A very important point is, a theoretical analysis will permit to know the exact resolution for each local twin-grating sensor

Interference Pattern Representation on the Complex s-Plane

In this work, the normalized interference pattern produced by a coherence interferometer system was represented as a complex function. The Laplace transform was applied for the transformation. Poles and zeros were determined from this complex function, and then, its pole-zero map and its Bode diagram were proposed. Both graphical representations were implemented numerically. From our numerical results, pole location and zero location depend on the optical path difference (OPD), while the Bode diagram gives us information about the OPD parameter. Based on the results obtained from the graphical representations, the coherence interferometer systems, the low-coherence interferometer systems, the interferometric sensing systems, and the fiber optic sensors can be analyze on the complex s-plane

CO and C 3

ZnSb2O6 has been synthesized by a microwave-assisted solution method in order to test its possible application as a gas sensor. Zinc nitrate, antimony trichloride, and ethylenediamine were used as precursors and deionized water as solvent. Microwave radiation, with a power of ~350 W, was applied for solvent evaporation. The thermal decomposition of the precursors leads to the formation of ZnSb2O6 at 600°C. This oxide crystallized in a tetragonal structure with cell parameters a=4.66 Å, c=9.26 Å and space group P42/mnm. Microwires and microrods formed by nanocrystals were observed by means of scanning and transmission electron microscopies (SEM and TEM, resp.). Pellets of the oxide were tested as gas sensors in flowing atmospheres of carbon monoxide (CO) and propane (C3H8). Sensitivity increased with the gas concentration (0–300 ppm) and working temperatures (ambient, 150 and 250°C) increase. The results indicate high sensitivity of ZnSb2O6 in both gases at different concentrations and operating temperatures

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Vectorial Image Representation for Image Classification

This paper proposes the transformation S→C→, where S is a digital gray-level image and C→ is a vector expressed through the textural space. The proposed transformation is denominated Vectorial Image Representation on the Texture Space (VIR-TS), given that the digital image S is represented by the textural vector C→. This vector C→ contains all of the local texture characteristics in the image of interest, and the texture unit T→ entertains a vectorial character, since it is defined through the resolution of a homogeneous equation system. For the application of this transformation, a new classifier for multiple classes is proposed in the texture space, where the vector C→ is employed as a characteristics vector. To verify its efficiency, it was experimentally deployed for the recognition of digital images of tree barks, obtaining an effective performance. In these experiments, the parametric value λ employed to solve the homogeneous equation system does not affect the results of the image classification. The VIR-TS transform possesses potential applications in specific tasks, such as locating missing persons, and the analysis and classification of diagnostic and medical images

Low-Finesse Fabry–Pérot Interferometers Applied in the Study of the Relation between the Optical Path Difference and Poles Location

Interferometry sensors are frequently analyzed by applying the Fourier transform because the transformation separates all frequency components of its signal, making its study on a complex plane feasible. In this work, we study the relation between the optical path difference (OPD) and poles location theoretically and experimentally, using the Laplace transform and a pole-zero map. Theory and experiments are in concordance. For our study, only the cosine function was considered, which is filtered from the interference pattern. In experimental work, two unperturbed low-finesse Fabry–Pérot interferometers were used. First, a Fabry–Pérot interferometer that has a cavity length of ~ 1.6 mm was used. Its optical path difference was 2.33 mm and the poles were localized at points ± i 12 . rad/nm. Secondly, a Fabry–Pérot interferometer with a cavity length of ~ 5.2 mm was used, and its optical path difference was 7.59 mm and the poles were localized at points ± i 40.4 rad/nm. Experimental results confirmed the theoretical analysis. Our proposal finds practical application for interferometer analysis, signal processing of optical fiber sensors, communication system analysis, and multiplexing systems based on interferometers

A Gas Sensor for Application as a Propane Leak Detector

A propane gas detector was built based on the semiconductor nickel antimonate oxide (NiSb2O6) by means of an analog electronic circuit. The gas detector was designed for monitoring atmospheres where the leakage of propane gas could possibly occur. The prototype’s construction methodology is presented in 5 stages: (1) synthesis of NiSb2O6 oxide powders, (2) characterization of the powders by XRD and TEM, (3) manufacture and electrical characterization of the chemical gas sensor, (4) design of the analog circuit based on the electrical response of the gas sensor, and (5) functionality tests. The gas detector was built at low cost and showed excellent functionality. The operating conditions were as follows: 200°C, gas concentration of 5 ppm, electronic circuit gain of 5, and sensor sensitivity of 0.41

Signal Analysis, Signal Demodulation and Numerical Simulation of a Quasi-Distributed Optical Fiber Sensor Based on FDM/WDM Techniques and Fabry-Pérot Interferometers

In civil engineering quasi-distributed optical fiber sensors are used for reinforced concrete monitoring, precast concrete monitoring, temperature monitoring, strain monitoring and temperature/strain monitoring. These quasi-distributed sensors necessarily apply some multiplexing technique. However, on many occasions, two or more multiplexing techniques are combined to increase the number of local sensors and then the cost of each sensing point is reduced. In this work, a signal analysis and a new signal demodulation algorithm are reported for a quasi-distributed optic fiber sensor system based on Frequency Division Multiplexing/Wavelength Division Multiplexing (FDM/WDM) and low-precision Fabry-Pérot interferometers. The mathematical analysis and the new algorithm optimize its design, its implementation, improve its functionality and reduce the cost per sensing point. The analysis was corroborated by simulating a quasi-distributed sensor in operation. Theoretical analysis and numerical simulation are in concordance. The optimization considers multiplexing techniques, signal demodulation, physical parameters, system noise, instrumentation, and detection technique. Based on our analysis and previous results reported, the optical sensing system can have more than 4000 local sensors and it has practical applications in civil engineering

Toxic Gas Detectors Based on a MnSb₂O₆ Oxide Chemical Sensor

We synthesized the semiconductor oxide MnSb2O6 through a wet chemical process assisted by low-power microwave radiation. A gas-sensitive sensor was elaborated from the MnSb2O6 powders obtained by calcination at 600°C. The sensor was electrically characterized in static CO and C3H8 atmospheres by measuring direct current signals at 100, 200, and 300°C. The toxic gases’ concentrations were 1, 5, 50, 100, 200, 300, 400, and 500 ppm of C3H8; and 1, 5, 50, 100, 200, and 300 ppm of CO. From the MnSb2O6’s electrical resistance results, a sensor’s operational point and a low-cost analog circuit were proposed, obtaining two new prototypes: one for detecting C3H8 and a second one for detecting CO. We selected the response at 200°C and 5 ppm for both cases. Notably, this concentration (5 ppm) is selectable with a calibration resistance, generating an alarm signal of ≈11.3V at a supply voltage of 120 V AC. The toxic gas detectors showed excellent functionality. The resistive sensor showed high sensitivity and good electrical response, while the analog circuit presented a rapid response. Due to the operating temperature employed (200°C), these devices could find practical applications, for example, exothermic generators and heaters

Sensitivity Tests of Pellets Made from Manganese Antimonate Nanoparticles in Carbon Monoxide and Propane Atmospheres

Nanoparticles of manganese antimonate (MnSb2O6) were prepared using the microwave-assisted colloidal method for its potential application as a gas sensor. For the synthesis of the oxide, manganese nitrate, antimony chloride, ethylenediamine and ethyl alcohol (as a solvent) were used. The precursor material was calcined at 800 °C in air and analyzed by X-ray diffraction. The oxide crystallized into a hexagonal structure with spatial group P321 and cell parameters a = b = 8.8054 Å and c = 4.7229 Å. The microstructure of the material was analyzed by scanning electron microscopy (SEM), finding the growth of microrods with a size of around ~10.27 μm and some other particles with an average size of ~1.3 μm. Photoacoustic spectroscopy (PAS) studies showed that the optical energy band (Eg) of the oxide was of ~1.79 eV. Transmission electron microscopy (TEM) analyses indicated that the size of the nanoparticles was of ~29.5 nm on average. The surface area of the powders was estimated at 14.6 m2/g by the Brunauer–Emmett–Teller (BET) method. Pellets prepared from the nanoparticles were tested in carbon monoxide (CO) and propane (C3H8) atmospheres at different concentrations (0–500 ppm) and operating temperatures (100, 200 and 300 °C). The pellets were very sensitive to changes in gas concentration and temperature: the response of the material rose as the concentration and temperature increased. The results showed that the MnSb2O6 nanoparticles can be a good candidate to be used as a novel gas sensor