Cardanol-Based Salophen-Modified Electrode for Analysing Nitric Oxide Bioavailability under Nitrosative Stress Conditions

High levels of nitric oxide (NO) can signal nitrosative stress, but its analysis is challenging considering the high reactivity, short half-life and transient behavior of this target molecule in biological milieu. In this work, a cardanol-based salophen-modified carbon paste electrode (CDN-salophen/MCPE) was developed and successfully applied to assess NO bioavailability in blood plasma of mice under induced stress. The results revealed that the modifier improved the device performance in terms of signal-to-noise ratio, charge-transport and fouling resistance. NO reactivity on CDN-salophen/MCPE was higher in 0.1 mol L‒1 H2SO4, and the resulting redox process involves adsorption steps that control the reaction kinetics. Monitoring molecule oxidation by square-wave voltammetry (100 s−1 frequency, 30 mV amplitude, 2 mV scan increment, after electrode preconditioning at 0.9 V for 15 s for analyte accumulation), it was possible to identify and quantify NO with great sensitivity (detection and quantification limit < 0.1 µmol L‒1) and low data variance (RSD ≤ 9.4% for repeatability and reproducibility tests), through a simple, fast and reliable electroanalytical protocol. The robustness acquired with CDN-salophen/MCPE allowed to detect changes in NO content in blood plasma during nitrosative stress, proving its efficiency for research on this subject.

Seasonal and microclimatic effects on leaf beetles (Coleoptera, Chrysomelidae) in a tropical forest fragment in northeastern Mexico

Leaf beetles (Coleoptera: Chrysomelidae) constitute a family of abundant, diverse, and ecologically important herbivorous insects, due to their high specificity with host plants, a close association with vegetation and a great sensitivity to microclimatic variation (factors that are modified gradually during the rainy and dry seasons). Therefore, the effects of seasonality (rainy and dry seasons) and microclimate on the community attributes of chrysomelids were evaluated in a semideciduous tropical forest fragment of northeastern Mexico. Monthly sampling was conducted, between March 2016 and February 2017, with an entomological sweep net in 18 plots of 20 × 20 m, randomly distributed from 320 to 480 m a.s.l. Seven microclimatic variables were simultaneously recorded during each of the samplings, using a portable weather station. In total, 216 samples were collected at the end of the study, of which 2,103 specimens, six subfamilies, 46 genera, and 71 species were obtained. The subfamily Galerucinae had the highest number of specimens and species in the study area, followed by Cassidinae. Seasonality caused significant changes in the abundance and number of leaf beetle species: highest richness was recorded in the rainy season, with 60 species, while the highest diversity (lowest dominance and highest H’ index) was obtained in the dry season. Seasonal inventory completeness of leaf beetles approached (rainy season) or was higher (dry season) than 70%, while the faunistic similarity between seasons was 0.63%. The outlying mean index was significant in both seasons; of the seven microclimatic variables analyzed, only temperature, heat index, evapotranspiration and wind speed were significantly related to changes in abundance of Chrysomelidae. Association between microclimate and leaf beetles was higher in the dry season, with a difference in the value of importance of the abiotic variables. The results indicated that each species exhibited a different response pattern to the microclimate, depending on the season, which suggests that the species may exhibit modifications in their niche requirements according to abiotic conditions. However, the investigations must be replicated in other regions, in order to obtain a better characterization of the seasonal and microclimatic influence on the family Chrysomelidae.

Plasma Formation and Its Parameters Used in Calibration-Free Laser-Induced Breakdown Spectroscopy

A rapidly developing technique over the last two years is laser induced break-down spectroscopy (LIBS), also known as laser-induced plasma spectroscopy (LIPS), a non-destructive spectroscopy technique that is mostly used for the analytical study of samples. With this technique, multiple elemental composition of elements are analyzed simultaneously without considering the form of sample that may be solid, liquid, or gas. Moreover, economically it is a very beneficial and valuable technique because no sample preparation is required, and sample consumption is very small. This technique is powerful enough that it can bore a microscopic crater usually in the solid samples to target. This technique has great sensitivity to find the resolution down to a single grain. It has a variety of applications in the field of science such as archeology, soils, environmental protection, and so on.

Research on material selection of force-sensitive element for high-frequency dynamic piezoelectric pressure sensor

The high-frequency dynamic piezoelectric pressure sensor has the advantages of simple structure, long service life, high natural frequency, excellent signal-to-noise ratio and great sensitivity. It is appropriate for measuring high dynamic, dynamic or quasi-static pressure changes and pressure fluctuations. And this kind of sensor is widely utilized in the shock wave testing. The force-sensitive element is one of the main factors affecting the static and dynamic performance of piezoelectric pressure sensors. Basing on the piezoelectric equation and coupling effect between mechanics and electricity, in this paper, the finite element model of the high-frequency dynamic piezoelectric pressure sensor is established. The influences of the force-sensing element on the sensitivity of the sensor are analysed. Referential suggestions for choosing force-sensitive element of high-frequency dynamic piezoelectric pressure sensor are provided.

Implementation and Validation of Hybrid Control for a DFIG Wind Turbine Using an FPGA Controller Board

In this study, a novel control approach for a doubly-fed induction generator (DFIG) is developed and applied to improve the system’s dynamic response and performance for providing high energy quality while avoiding harmonic accumulations. Because of its ease of implementation, field-oriented control (FOC) is frequently used. This control has great sensitivity to the machine’s parametric variations. For this reason, adaptive Backstepping control (ABC) is capable of preserving almost all of the performance and robustness properties. However, its analytical formulation has a problem. To overcome these disadvantages, the hybrid control (HC) is developed and verified to enable rapid response, complete reference tracking, and appropriate dynamic behavior with a low ripple level. This control is a combination of FOC’s and ABC’s control laws. The prepared control is explored by simulation testing using Matlab/Simulink and practical implementation using an FPGA board with actual turbine settings and a real wind profile of Dakhla City, Morocco. The results of hardware simulation show the efficacy of the HC in terms of speed and robustness, with a total harmonic distortion THD = 0.95, a value of THD that reveals the quality of the energy injected into the grid.

A sulfur dioxide Covariance-Based Retrieval Algorithm (COBRA): application to TROPOMI reveals new emission sources

Sensitive and accurate detection of sulfur dioxide (SO2) from space is important for monitoring and estimating global sulfur emissions. Inspired by detection methods applied in the thermal infrared, we present here a new scheme to retrieve SO2 columns from satellite observations of ultraviolet back-scattered radiances. The retrieval is based on a measurement error covariance matrix to fully represent the SO2-free radiance variability, so that the SO2 slant column density is the only retrieved parameter of the algorithm. We demonstrate this approach, named COBRA, on measurements from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (S-5P) satellite. We show that the method reduces significantly both the noise and biases present in the current TROPOMI operational DOAS SO2 retrievals. The performance of this technique is also benchmarked against that of the principal component algorithm (PCA) approach. We find that the quality of the data is similar and even slightly better with the proposed COBRA approach. The ability of the algorithm to retrieve SO2 accurately is further supported by comparison with ground-based observations. We illustrate the great sensitivity of the method with a high-resolution global SO2 map, considering 2.5 years of TROPOMI data. In addition to the known sources, we detect many new SO2 emission hotspots worldwide. For the largest sources, we use the COBRA data to estimate SO2 emission rates. Results are comparable to other recently published TROPOMI-based SO2 emissions estimates, but the associated uncertainties are significantly lower than with the operational data. Next, for a limited number of weak sources, we demonstrate the potential of our data for quantifying SO2 emissions with a detection limit of about 8 kt yr−1, a factor of 4 better than the emissions derived from the Ozone Monitoring Instrument (OMI). We anticipate that the systematic use of our TROPOMI COBRA SO2 column data set at a global scale will allow missing sources to be identified and quantified and help improve SO2 emission inventories.

An innovative neutron spectrometer for soil moisture measurements

Soil moisture is a crucial variable in evaluating soil properties and its interaction with the atmosphere, yet none of the techniques currently employed is fully adequate for evaluating the water content in soil over an area of hectares and depth of tens of centimeters. In recent times, it has been shown how the water content over this volume can be accurately assessed measuring changes in the epithermal flux of cosmic neutrons, which is extremely sensitive to the moderation caused by hydrogen. The instruments employed for neutron flux measurements are usually neutron counters, covered with moderator coatings for enhancing their sensitivity in the epithermal energy range. On the other hand, the worldwide shortage of $${}^{3}$$ 3 He caused a considerable increase in the costs associated with the manufacturing of proportional counters based on this gas, which were widely employed for their great sensitivity and noise rejection capability. In this work, we developed a $${}^{3}$$ 3 He-free neutron spectrometer for performing these measurements, which detects neutrons in the energy range from 0.01 ev to 1 GeV. The reconstruction of the energy spectrum allows a more accurate evaluation of the epithermal neutron flux and provides other information which improves the quality of soil moisture measurements. Irradiations performed with neutron sources of $${}^{241}$$ 241 Am and AmBe allowed to evaluate the spectrometric capability of the instrument, whereas the measurements of cosmic neutrons were employed to assess its sensitivity to cosmic radiation. The sensitivity of the instrument is slightly less than the one of the neutron counters currently employed, yet the access to the spectrometric information should provide greater accuracy in the epithermal flux measurements.

multiMarker: software for modelling and prediction of continuous food intake using multiple biomarkers measurements

Background Metabolomic biomarkers offer potential for objective and reliable food intake assessment, and there is growing interest in using biomarkers in place of or with traditional self-reported approaches. Ongoing research suggests that multiple biomarkers are associated with single foods, offering great sensitivity and specificity. However, currently there is a dearth of methods to model the relationship between multiple biomarkers and single food intake measurements. Results Here, we introduce multiMarker, a web-based application based on the homonymous R package, that enables one to infer the relationship between food intake and two or more metabolomic biomarkers. Furthermore, multiMarker allows prediction of food intake from biomarker data alone. multiMarker differs from previous approaches by providing distributions of predicted intakes, directly accounting for uncertainty in food intake quantification. Usage of both the R package and the web application is demonstrated using real data concerning three biomarkers for orange intake. Further, example data is pre-loaded in the web application to enable users to examine multiMarker’s functionality. Conclusion The proposed software advance the field of Food Intake Biomarkers providing researchers with a novel tool to perform continuous food intake quantification, and to assess its associated uncertainty, from multiple biomarkers. To facilitate widespread use of the framework, multiMarker has been implemented as an R package and a Shiny web application.

Influence of Oxidation on Fracture Toughness of Carbon-Carbon Composites for High-Temperature Applications

Carbon-Carbon Composites (C-CC), used as composites for their remarkable qualities in the space industry as well as in many other industry sectors. C-CC has proven to be the most efficient material in extreme temperature situations. One of the best high-temperature materials with good thermal quality, such as high-temperature stability, outstanding thermal conductivity and low-temperature expansion coefficients. In aircraft, railways, trucks and even race vehicles, C-CC brake disks are in high demand. In comparison to the favorable thermal and mechanical qualities of C-CC, their great sensitivity to oxidation in an oxidizing environment at temperatures even around 400°C is a major restriction with these composites. In particular, a study of the C-CC oxidation mechanism helps to create protective measures for these composites. The present experimental study explores the influence of oxidation in static air on the fracture toughness of C-CC. At a temperature of around 400°C to 700°C in an increase of 100°C, an oxidation evaluation of the material was carried out in static air. Results show a decrease in fracture toughness to increase in the temperature. We can observe that C-CC fracture toughness is severely affected by oxidation. The variation began at 400°C from 6% and was anticipated at 700°C up to 45%.

Parameter Identification from Normal and Pathological Middle Ears Using a Tailored Parameter Identification Algorithm

Current clinical practice is often unable to identify the causes of conductive hearing loss in the middle ear with sufficient certainty without exploratory surgery. Besides the large uncertainties due to interindividual variances, only partially understood cause-effect principles are a major reason for the hesitant use of objective methods such as wideband tympanometry in diagnosis, despite their high sensitivity to pathological changes. For a better understanding of objective metrics of the middle ear, this study presents a model that can be used to reproduce characteristic changes in metrics of the middle ear by altering local physical model parameters linked to the anatomical causes of a pathology. A finite-element model is therefore fitted with an adaptive parameter identification algorithm to results of a temporal bone study with stepwise and systematically prepared pathologies. The fitted model is able to reproduce well the measured quantities reflectance, impedance, umbo and stapes transfer function for normal ears and ears with otosclerosis, malleus fixation and disarticulation. In addition to a good representation of the characteristic influences of the pathologies in the measured quantities, a clear assignment of identified model parameters and pathologies consistent with previous studies is achieved. The identification results highlight the importance of the local stiffness and damping values in the middle ear for correct mapping of pathological characteristics, and address the challenges of limited measurement data and wide parameter ranges from literature. The great sensitivity of the model with respect to pathologies indicates a high potential for application in model-based diagnosis.