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Introduction: Air quality is directly affected by pollutant emission from vehicles, especially in large cities and metropolitan areas or when there is no compliance check for vehicle emission standards. Particulate Matter (PM) is one of the pollutants emitted from fuel burning in internal combustion engines and remains suspended in the atmosphere, causing respiratory and cardiovascular health problems to the population. In this study, we analyzed the interaction between vehicular emissions, meteorological variables, and particulate matter concentrations in the lower atmosphere, presenting methods for predicting and forecasting PM2.5. Methods: Meteorological and vehicle flow data from the city of Curitiba, Brazil, and particulate matter concentration data from optical sensors installed in the city between 2020 and 2022 were organized in hourly and daily averages. Prediction and forecasting were based on two machine learning models: Random Forest (RF) and Long Short-Term Memory (LSTM) neural network. The baseline model for prediction was chosen as the Multiple Linear Regression (MLR) model, and for forecast, we used the naive estimation as baseline. Results: RF showed that on hourly and daily prediction scales, the planetary boundary layer height was the most important variable, followed by wind gust and wind velocity in hourly or daily cases, respectively. The highest PM prediction accuracy (99.37%) was found using the RF model on a daily scale. For forecasting, the highest accuracy was 99.71% using the LSTM model for 1-h forecast horizon with 5 h of previous data used as input variables. Discussion: The RF and LSTM models were able to improve prediction and forecasting compared with MLR and Naive, respectively. The LSTM was trained with data corresponding to the period of the COVID-19 pandemic (2020 and 2021) and was able to forecast the concentration of PM2.5 in 2022, in which the data show that there was greater circulation of vehicles and higher peaks in the concentration of PM2.5. Our results can help the physical understanding of factors influencing pollutant dispersion from vehicle emissions at the lower atmosphere in urban environment. This study supports the formulation of new government policies to mitigate the impact of vehicle emissions in large cities.

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This work reports the development and application of a highly selective core@shell-based quantum dot-molecularly imprinted polymer (QD@MIP) sensor for the detection of sulfadiazine (SDZ)-an antibiotic which belongs to the sulfonamide family. The synthesis of the smart material or MIP (molecularly imprinted polymer) was carried out by a precipitation method directly on the quantum dot surface, which played the role of a fluorescent probe in the optical sensor. The synthesized polymer was characterized by scanning electron microscopy and Fourier transform infrared spectroscopy. Fluorescence experiments were performed in order to evaluate the effects of pH, interaction time of the QD@MIP with the analyte and SDZ concentration in different matrices. Under optimized conditions, a linear concentration range of 10.0-60.0 ppm and a limit of detection of 3.33 ppm were obtained. The repeatability and reproducibility of the proposed QD@MIP were evaluated in terms of the RSD, where RSD values of less than 5% were obtained in both tests. Selectivity studies were carried out in the presence of four possible interfering substances with quenching properties, and the signals obtained for these interferents confirmed the excellent selectivity of the proposed sensor; the imprinting factor value obtained for SDZ was 1.64. Finally, the proposed sensor was applied in real animal-based food samples using a spiked concentration of SDZ, where the recovery values obtained were above 90% (experiments were performed in triplicate).

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This paper describes the use of an optical instrument, the Fabry-Perot interferometer, adapted to measure very low pressures. The interferometer consists of two high-reflectance flat mirrors placed one in front of another. In addition, a metallic chamber contains air or a gas. In one of the faces of the chamber, a flexible thin silicone membrane is attached and, over it, one of the mirrors is glued. The other mirror rests in a fixed mechanical mounting. Light crosses both mirrors and, when it leaves them, forms an interference pattern consisting of concentric circular fringes. When the pressure is increased/decreased within the chamber, a displacement of the fringes is observed due to the movement of the glued mirror. By measuring the fringe displacement and knowing the pressure, a calibration plot can be made. Minimum pressure measurements of about tens of Pascals were achieved.

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Therapeutic intervention to skin wounds requires covering the affected area with wound dressings. Interdisciplinary efforts have focused on the development of smart bandages that can perform multiple functions. In this direction, here, we designed a low cost (U$0.012 per cm2) multifunctional therapeutic wound dressing fabricated by loading curcumin (CC) into poly(ϵ-caprolactone) (PCL) nanofibers using solution blow spinning (SBS). The freestanding PCL/CC bandages were characterized by distinct physicochemical approaches and were successful in performing varied functions, including controlled release of CC, colorimetric indication of the wound conditions, barrier against microorganisms, being biocompatible, and providing a photosensitive platform for antimicrobial photodynamic therapy (aPDT). The chemical nature of PCL and CC and the interactions between these components allowed CC to be released for 192 h (ca. 8 days), which could be correlated with the Korsmeyer-Peppas model, with a burst release suitable to treat the inflammatory phase. Due to the CC keto-enol tautomerism, an optical indication of the healing status could be obtained using PCL/CC, which occurred immediately, ranging between red/orange and yellow shades. The effect against pathogenic microorganisms evaluated by agar disc-diffusion, affected skin wound simulation (ex vivo), and microbial penetration tests demonstrated the ability to block and inhibit microbial permeation in different environments. The biocompatibilities of PCL and PCL/CC were verified by in vitro cytotoxicity study, which demonstrated that cell viabilities average above 94 and 96% for human dermal fibroblasts. In addition, the proposed bandage responded to aPDT applied to an in vivo assay, showing that, when irritated, PCL/CC was able to reduce the bacteria present on the real wound of mice. In summary, our findings demonstrate that using PCL and CC to produce nonwovens by the SBS technique offers potential for the rapid fabrication of biocompatible and multifunctional wound dressings, paving the way for large-scale production and utilization of such dressings in the treatment of skin wounds.

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The published data correspond to images of simulated specklegrams, which result from the calculation of the modal interference that occurs in a multimode optical fiber. These have a characteristic pattern due to the constructive or destructive interference between the light modes depending on their phase differences. The specklegram contains valuable information since the propagation of the modes varies according to the influence of some external disturbances, and therefore, the speckle pattern changes. This dataset contains specklegrams that vary according to the temperature. These data have been obtained by simulation using the finite element method (FEM) through the COMSOL multiphysics platform. In the simulation, the vector wave equation is solved, and the refractive index of the fiber is recalculated due to the temperature change. We simulated a 1490 nm wavelength laser, an optical fiber with a core diameter of 50 µm and cladding diameter of 125 µm. The dataset contains specklegrams covering the range of temperatures from 0°C to 120°C in 0.2°C steps.

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A refractive index sensor based on an on-chip silicon nitride (Si3N4) ridge waveguide long-range surface plasmon polariton (LRSPP) is theoretically designed. The waveguide sensor consists of a gold film to enable the plasmonic resonance on top of a Cytop polymer layer. A proper finite element method was used to design and optimize the geometric parameters at the optical wavelength of 633 nm. In addition, the spectral performance was evaluated using the transfer matrix method from 580 to 680 nm. The redshifted interference spectrum results from an increasing analyte refractive index. The sensitivities of 6313 dB/cm/RIU and 251.82 nm/RIU can be obtained with a 400 nm wide and 25 nm thick Au layer. The proposed sensor has the potential for point-of-care applications considering its compactness and simplicity of construction.

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This study determined whether Canopeo and GreenSeeker measurements in Megathyrsus maximus can estimate plant height, dry matter mass, morphological components, and content of crude protein and neutral detergent fiber at different days of growth. Five plots of 5 × 25m M. maximus grass were defined: subplots of 1×1m were evaluated every three days, in which the pasture shows 3, 6, 9, 12, 15, 18, 21, 24, 27, and 30 days of regrowth. The subplot was evaluated for canopy height and mass accumulation. The canopeo index (CI) obtained at a higher height was lower than those obtained at a smaller height. Higher measurement height increased the normalized difference vegetation index (NDVI) relative to 0.10 m. The highest indexes were observed since 18 d of regrowth. Except for the CI evaluated at 0.10 m of height, the indexes were not correlated to the chemical composition of the forage. The CI and NDVI were positively correlated to plant height, dry matter mass, and leaf index, whereas both were negatively correlated with stalk index. Thus, lower evaluation heights for CI and NDVI can be a good predictor of forage height. Values of 0.83 and 85.8 for NDVI and CI, respectively, indicated an appropriate time to start the grazing of M. maximus.

O presente estudo teve como objetivo avaliar se os índices obtidos com Canopeo e GreenSeeker (NDVI) em Megathyrsus maximum são capazes de estimar altura de plantas, massa de matéria seca, componentes morfológicos e teor de proteína bruta e fibra em detergente neutro em diferentes dias de crescimento. Cinco parcelas de 5 × 25 m de capim M.maximum foram definidas: sub parcelas de 1 × 1 m foram avaliadas a cada três dias, nas quais a pastagem apresenta 3, 6, 9, 12, 15, 18, 21, 24, 27 e 30 dias de rebrota. A sub parcela foi avaliada quanto à altura do dossel e acúmulo de massa. O índice do Canopeo (IC) obtido em maior altura foi menor do que o obtido em menor altura. A maior altura de medição aumentou o NDVI em relação a 0,10 m. Os maiores índices foram observados desde 18 dias de rebrota. Exceto para o IC avaliado a 0,10 m de altura, os índices não foram correlacionados com a composição química da forragem. IC e NDVI correlacionaram-se positivamente com a altura da planta, massa de MS e índice foliar, e negativamente com o índice de colmos. Assim, menores alturas de avaliação para IC e NDVI podem ser um bom preditor da altura da forragem. Valores de 0,83 e 85,8 para NDVI e IC, respectivamente, indicam um momento adequado para o início do pastejo de Megathyrsus maximum.

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ABSTRACT: This study determined whether Canopeo and GreenSeeker measurements in Megathyrsus maximus can estimate plant height, dry matter mass, morphological components, and content of crude protein and neutral detergent fiber at different days of growth. Five plots of 5 × 25m M. maximus grass were defined: subplots of 1×1m were evaluated every three days, in which the pasture shows 3, 6, 9, 12, 15, 18, 21, 24, 27, and 30 days of regrowth. The subplot was evaluated for canopy height and mass accumulation. The canopeo index (CI) obtained at a higher height was lower than those obtained at a smaller height. Higher measurement height increased the normalized difference vegetation index (NDVI) relative to 0.10 m. The highest indexes were observed since 18 d of regrowth. Except for the CI evaluated at 0.10 m of height, the indexes were not correlated to the chemical composition of the forage. The CI and NDVI were positively correlated to plant height, dry matter mass, and leaf index, whereas both were negatively correlated with stalk index. Thus, lower evaluation heights for CI and NDVI can be a good predictor of forage height. Values of 0.83 and 85.8 for NDVI and CI, respectively, indicated an appropriate time to start the grazing of M. maximus.

RESUMO: O presente estudo teve como objetivo avaliar se os índices obtidos com Canopeo e GreenSeeker (NDVI) em Megathyrsus maximum são capazes de estimar altura de plantas, massa de matéria seca, componentes morfológicos e teor de proteína bruta e fibra em detergente neutro em diferentes dias de crescimento. Cinco parcelas de 5 × 25 m de capim M.maximum foram definidas: sub parcelas de 1 × 1 m foram avaliadas a cada três dias, nas quais a pastagem apresenta 3, 6, 9, 12, 15, 18, 21, 24, 27 e 30 dias de rebrota. A sub parcela foi avaliada quanto à altura do dossel e acúmulo de massa. O índice do Canopeo (IC) obtido em maior altura foi menor do que o obtido em menor altura. A maior altura de medição aumentou o NDVI em relação a 0,10 m. Os maiores índices foram observados desde 18 dias de rebrota. Exceto para o IC avaliado a 0,10 m de altura, os índices não foram correlacionados com a composição química da forragem. IC e NDVI correlacionaram-se positivamente com a altura da planta, massa de MS e índice foliar, e negativamente com o índice de colmos. Assim, menores alturas de avaliação para IC e NDVI podem ser um bom preditor da altura da forragem. Valores de 0,83 e 85,8 para NDVI e IC, respectivamente, indicam um momento adequado para o início do pastejo de Megathyrsus maximum.

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In many areas, the analysis of a cylindrical structure is necessary, and a form to analyze it is by evaluating the diameter changes. Some areas can be cited: pipelines for oil or gas distribution and radial growth of trees whose diameter changes are directly related to irrigation and the radial expansion since it depends on the water soil deficit. For some species, these radial variations can change in around 5 mm. This paper proposes and experimentally investigates a sensor based on a core diameter mismatch technique for diameter changes measurement. The sensor structure is a combination of a cylindrical piece developed using a 3D printer and a Mach-Zehnder interferometer. The pieces were developed to assist in monitoring the diameter variation. It is formed by splicing an uncoated short section of MMF (Multimode Fiber) between two standard SMFs (Singlemode Fibers) called SMF-MMF-SMF (SMS), where the MMF length is 15 mm. The work is divided into two main parts. Firstly, the sensor was fixed at two points on the first developed piece, and the diameter reduction caused dips or peaks shift of the transmittance spectrum due to curvature and strain influence. The fixation point (FP) distances used are: 5 mm, 10 mm, and 15 mm. Finally, the setup with the best sensitivity was chosen, from first results, to develop another test with an optimization. This optimization is performed in the printed piece where two supports are created so that only the strain influences the sensor. The results showed good sensitivity, reasonable dynamic range, and easy setup reproduction. Therefore, the sensor could be used for diameter variation measurement for proposed applications.

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In this work, a red, green, blue (RGB) color sensor was used for quantitative optical analysis of colored solutions. The capability of the sensor to respond to different colored solutions was critically evaluated to better understand which spectral bands are filtered and processed by each sensor channel. The effective capability of the RGB sensor, defined as its ability to illuminate and detect electromagnetic radiation reflected by the samples, was observed in the range of 415-564, 440-600 and 510-750 nm for blue, green and red channels, respectively. These results can help understand the interaction between the light emitted by the sensor and the signals obtained by the RGB channels for different quantitative determinations. In order to investigate the interaction between the RGB sensor and colored substances, and thereafter achieve quantitative optical analysis, different colored dyes were chosen to evaluate the RGB sensor capability, thus covering a wide range of colors. The analytical performance of the RGB sensor yielded a linear range of 5.0-50.0 µmol L-1 for dye solutions. The accuracy of this sensor was demonstrated by the thiocyanate method for colorimetric determination of iron in soil and supplement samples. Such RGB sensor achieved analytical performance similar to that obtained with the commercial spectrophotometer, without requiring the use of computers for image processing so as to gather RGB values. Additionally, this sensor also contributes to meeting the requirements of Internet of Analytical Things (IoAT) for the quantitative analysis of colored solutions.

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The biophysical characteristics of vegetative canopies, such as biomass, height, and canopy diameter, are of paramount importance for the study of the development and productive behavior of crops. Faced with a scarcity of studies aimed at estimating these parameters, the objective of this study was to evaluate the performance of artificial neural networks (ANNs) applied to Proximal Remote Sensing (PRS) to estimate biophysical characteristics of soybean culture. The data used to train and validate the ANNs came from an experiment composed of 65 plots with 30 x 30 m mesh, its development was carried out in the 2016/2017 crop in the Brazilian agricultural area. The evaluations were carried out at 30, 45, 60, and 75 days after sowing (DAS), monitoring the spatial and temporal variability of the biophysical characteristics of the soybean crop. Vegetation indexes were collected using canopy sensors. The accuracy and precision were determined by the coefficient of determination (R2) and the error of the forecasts by MAPE (Mean Absolute Percentage Error). PRS and ANNs showed high potential for application in agriculture, since they obtained good performance in the estimation of height (R2 = 0.89) and canopy diameter (R2 = 0.96), being fresh biomass (R2 =0.98) and dry biomass (R2 = 0.97) were the best-estimated variables.

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Sensors based on polarization are suitable for application in power grids due to their excellent characteristics, such as high electrical insulation, non-magnetic saturation, oil-free, no risk of explosive failures, and high bandwidth. Utility companies are incorporating new technologies that are driving the evolution of electrical systems. Thus, it is interesting to evaluate the possibility of using polarization sensors in a network configuration. In this work, we present an experimental study of a current and voltage polarization sensor network applied to a medium voltage distribution grid. The current sensor is based on the Faraday effect, and the voltage sensor uses the Pockels effect. Both sensors use a 90° polarization degree between the two output ports to compensate for the various impairments on the measurements by applying the difference-over-sum. The network uses a DWDM topology centered at the 1550 nm range, and both current and voltage sensors in this work used this spectral band. We evaluated the sensor node in terms of accuracy according to IEC standard 61869-10 and IEC standard 61869-11. Considering that an important application of this sensor network is in the aerial cable of medium voltage networks, sensor node accuracy was also estimated in the presence of cable vibration. The calculated power budget of the proposed network indicates that reaching ten nodes of current and voltage sensors in a 10 km optical link is possible, which is enough for a medium urban voltage distribution network.

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Sensors and biosensors play a key role as an analytical tool for the rapid, reliable, and early diagnosis of human diseases. Such devices can also be employed for monitoring environmental pollutants in air and water in an expedited way. More recently, nanomaterials have been proposed as an alternative in sensor fabrication to achieve gains in performance in terms of sensitivity, selectivity, and portability. In this direction, the use of cellulose nanomaterials (CNM), such as cellulose nanofibrils (CNF), cellulose nanocrystals (CNC), and bacterial cellulose (BC), has experienced rapid growth in the fabrication of varied types of sensors. The advantageous properties are related to the supramolecular structures that form the distinct CNM, their biocompatibility, and highly reactive functional groups that enable surface functionalization. The CNM can be applied as hydrogels and xerogels, thin films, nanopapers and other structures interesting for sensor design. Besides, CNM can be combined with other materials (e.g., nanoparticles, enzymes, carbon nanomaterials, etc.) and varied substrates to advanced sensors and biosensors fabrication. This review explores recent advances on CNM and composites applied in the fabrication of optical, electrical, electrochemical, and piezoelectric sensors for detecting analytes ranging from environmental pollutants to human physiological parameters. Emphasis is given to how cellulose nanomaterials can contribute to enhance the performance of varied sensors as well as expand novel sensing applications, which could not be easily achieved using standard materials. Finally, challenges and future trends on the use of cellulose-based materials in sensors and biosensors are also discussed.

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BACKGROUND: In this work, a detector based on optical fiber covered with Multi-Wall Carbon Nanotubes (MWCNTs) was used for sensing and removal of Alizarin from wastewaters. Alizarin is a strong anionic red dye that is part of the anthraquinone dye group. As a rule, this dye is used in the textile industry as a coloring agent. Experiments showed a good efficiency of wastewater treatment. This development could resolve the problem of water contamination with Alizarin red dye. METHODS: We used a single-mode fiber SMF-28e with a core diameter of 8.2 µm and a cladding diameter of 125 µm as a base for the tapered optical fiber detector. An MWCNTs array was synthesized on the tapered optical fiber detector surface by spray pyrolysis Chemical Vapor Deposition (CVD) method at 800oC for 20 min inside a tubular furnace, using ferrocene solution in toluene as a catalyst precursor. The formed structure was applied for Alizarin detection in water. RESULTS: According to the patent studies, the nanotubes completely covered the optical fiber surface and the array had a high density with minimal distance between nearby nanotubes. Carbon nanotubes were oriented along the radius of the optical fiber. The average diameter of carbon nanotubes was 24 nm. The optical absorbance levels increased as the Alizarin concentration increased from 50 mg/L to 1000 mg/L. MWCNTs on the optical fiber tapered section adsorbed the dye molecules from aqueous solution. Three intensive absorption bands with the wavelength of the 700, 714 and 730 nm appeared and their intensity increased as the Alizarin concentration increased. The accumulated Alizarin can be recovered by multiple immersing clean water. This property may make tapered optical fiber detector reusable and increase the economic expediency of the sensor application. CONCLUSION: The study showed higher Alizarin adsorption efficiency of the tapered optical fiber detector compared with relative detectors. This structure can be reusable for dye detection. Removal efficiency for Alizarin reached 98.6%, which makes the tapered optical fiber detector promising for wastewater treatment and dye elimination.

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Hydrogen peroxide (H2O2) is an important compound for several industrial sectors, but it becomes harmful to human health under high concentrations. Thus, the development of simple, low cost and fast analytical methods capable to detect and monitor H2O2 is fundamentally important. In the present study, we report a simple route for synthesizing silver nanoparticles (AgNPs) in the presence of a nanostructured polysaccharide (cellulose nanowhiskers) to produce a hybrid material, which was employed as a colorimetric probe for H2O2 detection. Our results revealed that AgNPs tend to experience catalytic decomposition when exposed to H2O2, causing a decrease of AgNPs absorption band at 410 nm in accordance with H2O2 concentration. This decrease was linearly dependent on H2O2 concentration (in the ranges 0.01-30 µM and 60-600 µM), yielding limits of detection of 0.014 µM and 112 µM, respectively. The easy-to-interpret H2O2 sensor also proved to be suitable for real samples analysis even in the presence of other interfering substances.

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As consumption of fish and fish-based foods increases, non-destructive monitoring of fish freshness also becomes more prominent. Fish products are very perishable and prone to microbiological growth, not always easily detected by organoleptic evaluation. The analysis of the headspace of fish specimens through gas sensing is an interesting approach to monitor fish freshness. Here we report a gas sensing method for monitoring Tilapia fish spoilage based on the application of a single gas sensitive gel material coupled to an optical electronic nose. The optical signals of the sensor and the extent of bacterial growth were followed over time, and results indicated good correlation between the two determinations, which suggests the potential application of this simple and low cost system for Tilapia fish freshness monitoring.

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RESUMO Neste estudo foram avaliados os efeitos do tamanho da partícula e de variações da concentração de sedimentos suspensos (CSS) sobre as leituras de turbidez de três sensores óptico-nefelométricos, com iguais características ópticas e geométricas, utilizando amostras de sedimentos suspensos coletadas na seção fluviométrica da bacia do Turcato (19,5 km²), localizada na Região Sul do Brasil. O material coletado passou por processos de peneiramento e pipetagem para fracionamento nas granulometrias areia e silte. Para cada diâmetro foram separadas frações com diferentes concentrações de sedimentos, variando entre 0,01 e 5,00 g.L-1. Os resultados demonstram grande influência da CSS e do tamanho da partícula sobre a turbidez. Para qualquer situação, o aumento da turbidez é inverso ao tamanho da partícula e diretamente relacionado ao aumento da CSS. As variações da turbidez, expressas em função da CSS (sensibilidade do sensor), são maiores para menores diâmetros, atingindo valores quase constantes para partículas de areia. As leituras de turbidez dos três sensores não apresentaram diferença significativa no nível de 5% pelo teste de Mann-Whitney rank sum . Para uma mesma CSS, a leitura de turbidez pode ser diferente, conforme a classe granulométrica analisada. A turbidez registrada pelo sensor para a classe silte equivale a uma turbidez observada para uma CSS dez vezes menor para a classe das areias.

ABSTRACT This study evaluates the effects of particle size and variations of CSS on turbidity readings of three optical-nephelometric sensors using sediment samples collected in the field. Samples were collected in fluviometric station at Turcato basin (19.5 km²), located in the South region of Brazil. The collected material underwent screening and pipetting processes for fractionation in sand and silt grain size. For each diameter were separated fractions with different sediment concentration ranging between 0.01 and 5.00 g.L-1. The results demonstrate great influence of CSS and particle size on turbidity readings. The increase in turbidity is opposite to particle size and directly related to CSS. Variations in turbidity, expressed in CSS function (sensor sensitivity), are higher for smaller diameters, reaching almost constant values for sand particles. Turbidity readings of the three sensors showed no significant difference in the level of 5% by the Mann-Whitney rank sum test. For a given CSS, the turbidity reading may be different, depending on the granulometric class analyzed. Turbidity recorded by the sensor to the silt-class is equivalent to a sensor response observed for a CSS ten times lower for the sand class.

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This article describes the application and performance of an inexpensive, simple and portable device for colorimetric quantitative determination of drugs in pharmaceutical preparations. The sensor is a light detector resistor (LDR) incorporated into a black PTFE cell and coupled to a low-cost multimeter (Ohmmeter). Quantitative studies were performed with captopril/p-chloranil/H2O2 and methyldopa/ammonium molybdate systems. Calibration curves were obtained by plotting the electrical resistance of the LDR against the concentration of the colored species in the ranges 1.84 × 10-4 to 1.29 × 10-3mol L-1 and 5.04 × 10-4 to 2.52 × 10-3 mol L-1 for captopril/p-chloranil/H2O2 and methyldopa/ammonium molybdate systems, respectively, exhibiting good coefficients of determination. Statistical analysis of the results obtained showed no significant difference between the proposed methodologies and the official reported methods, as evidenced by the t-test and variance ratio at a 95% confidence level. The results of this study demonstrate the applicability of the instrument for simple, accurate, precise, fast,in situ and low-cost colorimetric analysis of drugs in pharmaceutical products.

Este artigo descreve o desenvolvimento e a aplicação de um dispositivo portátil, simples e barato para a determinação colorimétrica quantitativa de fármacos em formulações farmacêuticas. O sensor é um resistor detector de luz (RDL) colocado numa célula de PTFE e acoplado a um multímetro de baixo custo. Os estudos quantitativos foram realizados utilizando captopril/p-cloranil/H2O2 e metildopa/molibdato de amônio como sistemas reacionais. As curvas de calibração foram obtidas através da representação gráfica da resistência elétrica do RDL contra a concentração dos complexos coloridos formados nas faixas de 1,84 × 10-4 e 1,29 × 10-3 mol L-1 e 5,04 × 10-4 e 2,52 × 10- 3 mol L-1 para captopril/p-cloranil/H2O2 e de metildopa/molibdato de amônio, respectivamente, com bons coeficientes de determinação. As análises estatísticas dos resultados obtidos mostraram que não houve diferença significativa entre os métodos propostos e os métodos oficiais como evidente a partir dos testes "t-Student" eF-Fisher, com nível de confiança de 95%. Os resultados deste estudo demonstram que o instrumento proposto neste trabalho é simples, de fácil operação, baixo custo e apresentou boa exatidão e boa precisão para o doseamento de fármacos em medicamentos.

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Power transformers are essential for a functioning electrical system and therefore require special attention by maintenance programs because a fault can harm both the company and society. The temperature inside a power transformer and the dissolved gases, which are primarily composed of acetylene, are the two main parameters monitored when detecting faults. This paper describes the development of a device for analyzing the acetylene content in insulating oil using spectrofluorimetry. Using this device introduces a new methodology for the maintaining and operating power transformers. The prototype is currently operating in a substation. The results presented by this system were satisfactory; when compared to chromatographic data, the errors did not exceed 15%. This prototype may be used to confirm the quality of an insulating oil sample to detect faults in power transformers.