Noise Tolerant Photonic Bowtie Grating Environmental Sensor

Resonant photonic refractive index sensors have made major advances based on their high sensitivity and contact-less readout capability, which is advantageous in many areas of science and technology. A major issue for the technological implementation of such sensors is their response to external influences, such as vibrations and temperature variations; the more sensitive a sensor, the more susceptible it also becomes to external influences. Here, we introduce a novel bowtie-shaped sensor that is highly responsive to refractive index variations while compensating for temperature changes and mechanical (linear and angular) vibrations. We exemplify its capability by demonstrating the detection of salinity to a precision of 0.1%, corresponding to 2.3 × 10-4 refractive index units in the presence of temperature fluctuations and mechanical vibrations. As a second exemplar, we detected bacteria growth in a pilot industrial environment. Our results demonstrate that it is possible to translate high sensitivity resonant photonic refractive index sensors into real-world environments.

A Self-Temperature Compensation Barometer Based on All-Quartz Resonant Pressure Sensor

This paper reports a self-temperature compensation barometer based on a quartz resonant pressure sensor. A novel sensor chip that contains a double-ended tuning fork (DETF) resonator and a single-ended tuning fork (SETF) resonator is designed and fabricated. The two resonators are designed on the same diaphragm. The DETF resonator works as a pressure sensor. To reduce the influence of the temperature drift, the SETF resonator works as a temperature compensation sensor, which senses the instantaneous temperature of the DETF resonator. The temperature compensation method based on polynomial fitting is studied. The experimental results show that the accuracy is 0.019% F.S. in a pressure range of 200~1200 hPa over a temperature range of -20 °C~+60 °C. The absolute errors of the barometer are within ±23 Pa. To verify its actual performance, a drone flight test was conducted. The test results are consistent with the actual flight trajectory.

Advancing Slim-Hole Drilling Accuracy: A C-I-WOA-CNN Approach for Temperature-Compensated Pressure Measurements

This paper presents a novel method to improve drill pressure measurement accuracy in slim-hole drilling within the petroleum industry, a sector often plagued by extreme conditions that compromise data integrity. We introduce a temperature compensation model based on a Chaotic-Initiated Adaptive Whale Optimization Algorithm (C-I-WOA) for optimizing Convolutional Neural Networks (CNNs), dubbed the C-I-WOA-CNN model. This approach enhances the Whale Optimization Algorithm (WOA) initialization through chaotic mapping, boosts the population diversity, and features an adaptive weight recalibration mechanism for an improved global search and local optimization. Our results reveal that the C-I-WOA-CNN model significantly outperforms traditional CNNs in its convergence speed, global searching, and local exploitation capabilities, reducing the average absolute percentage error in pressure parameter predictions from 1.9089% to 0.86504%, thereby providing a dependable solution for correcting temperature-induced measurement errors in downhole settings.

The Design and Experimentation of a Corn Moisture Detection Device Based on Double Capacitors

Detecting the moisture content of grain accurately and rapidly has important significance for harvesting, transport, storage, processing, and precision agriculture. There are some problems with the slow detection speeds, unstable detection, and low detection accuracy of moisture contents in corn harvesters. In that case, an online moisture detection device was designed, which is based on double capacitors. A new method of capacitance complementation and integration was proposed to eliminate the limitation of single data. The device is composed of a sampling mechanism and a double-capacitor sensor consisting of a flatbed capacitor and a cylindrical capacitor. The optimum structure size of the capacitor plates was determined by simulation optimization. In addition to this, the detection system with software and hardware was developed to estimate the moisture content. Indoor dynamic measurement tests were carried out to analyze the influence of temperature and porosity. Based on the influencing factors and capacitance, a model was established to estimate the moisture content. Finally, the support vector machine (SVM) regressions between the capacitance and moisture content were built up so that the R2 values were more than 0.91. In the stability test, the standard deviation of the stability test was 1.09%, and the maximum relative error of the measurement accuracy test was 1.22%. In the dynamic verification test, the maximum error of the measurement was 4.62%, less than 5%. It provides a measurement method for the accurate, rapid, and stable detection of the moisture content of corn and other grains.

Sensor-Integrated Chairs for Lower Body Strength and Endurance Assessment

This paper describes an automated method and device to conduct the Chair Stand Tests of the Fullerton Functional Test Battery. The Fullerton Functional Test is a suite of physical tests designed to assess the physical fitness of older adults. The Chair Stand Tests, which include the Five Times Sit-to-Stand Test (5xSST) and the 30 Second Sit-to-Stand Test (30CST), are the standard for measuring lower-body strength in older adults. However, these tests are performed manually, which can be labor-intensive and prone to error. We developed a sensor-integrated chair that automatically captures the dynamic weight and distribution on the chair. The collected time series weight-sensor data is automatically uploaded for immediate determination of the sit-to-stand timing and counts, as well as providing a record for future comparison of lower-body strength progression. The automatic test administration can provide significant labor savings for medical personnel and deliver much more accurate data. Data from 10 patients showed good agreement between the manually collected and sensor-collected 30CST data (M = 0.5, SD = 1.58, 95% CI = 1.13). Additional data processing will be able to yield measurements of fatigue and balance and evaluate the mechanisms of failed standing attempts.

Trend Decomposition for Temperature Compensation in a Radar-Based Structural Health Monitoring System of Wind Turbine Blades

The compensation of temperature is critical in every structural health monitoring (SHM) system for achieving maximum damage detection performance. This paper analyses a novel approach based on seasonal trend decomposition to eliminate the temperature effect in a radar-based SHM system for wind turbine blades that operates in the frequency band from 58 to 63.5 GHz. While the original seasonal trend decomposition searches for the trend of a periodic signal in its entirety, the new method uses a moving average to determine trends for each point of a periodic signal. The points of the seasonal signal no longer need to have the same trend. Based on the determined trends, the measurement signal can be corrected by temperature effects, providing accurate damage detection results under changing temperature conditions. The performance of the trend decomposition is demonstrated with experimental data obtained during a full-scale fatigue test of a 31 m long wind turbine blade subjected to ambient temperature variations. For comparison, the well-known optimal baseline selection (OBS) approach is used, which is based on multiple baseline measurements at different temperature conditions. The use of metrics, such as the contrast in damage indicators, enables the performance assessment of both methods.

Temperature Compensation of Laser Methane Sensor Based on a Large-Scale Dataset and the ISSA-BP Neural Network

We aimed to improve the detection accuracy of laser methane sensors in expansive temperature application environments. In this paper, a large-scale dataset of the measured concentration of the sensor at different temperatures is established, and a temperature compensation model based on the ISSA-BP neural network is proposed. On the data side, a large-scale dataset of 15,810 sets of laser methane sensors with different temperatures and concentrations was established, and an Improved Isolation Forest algorithm was used to clean the large-scale data and remove the outliers in the dataset. On the modeling framework, a temperature compensation model based on the ISSA-BP neural network is proposed. The quasi-reflective learning, chameleon swarm algorithm, Lévy flight, and artificial rabbits optimization are utilized to improve the initialization of the sparrow population, explorer position, anti-predator position, and position of individual sparrows in each generation, respectively, to improve the global optimization seeking ability of the standard sparrow search algorithm. The ISSA-BP temperature compensation model far outperforms the four models, SVM, RF, BP, and PSO-BP, in model evaluation metrics such as MAE, MAPE, RMSE, and R-square for both the training and test sets. The results show that the algorithm in this paper can significantly improve the detection accuracy of the laser methane sensor under the wide temperature application environment.

Machine learning reveals singing rhythms of male Pacific field crickets are clock controlled

Circadian rhythms are ubiquitous in nature and endogenous circadian clocks drive the daily expression of many fitness-related behaviors. However, little is known about whether such traits are targets of selection imposed by natural enemies. In Hawaiian populations of the nocturnally active Pacific field cricket (Teleogryllus oceanicus), males sing to attract mates, yet sexually selected singing rhythms are also subject to natural selection from the acoustically orienting and deadly parasitoid fly, Ormia ochracea. Here, we use T. oceanicus to test whether singing rhythms are endogenous and scheduled by circadian clocks, making them possible targets of selection imposed by flies. We also develop a novel audio-to-circadian analysis pipeline, capable of extracting useful parameters from which to train machine learning algorithms and process large quantities of audio data. Singing rhythms fulfilled all criteria for endogenous circadian clock control, including being driven by photoschedule, self-sustained periodicity of approximately 24 h, and being robust to variation in temperature. Furthermore, singing rhythms varied across individuals, which might suggest genetic variation on which natural and sexual selection pressures can act. Sexual signals and ornaments are well-known targets of selection by natural enemies, but our findings indicate that the circadian timing of those traits' expression may also determine fitness.

Comparison and Verification of Three Algorithms for Accuracy Improvement of Quartz Resonant Pressure Sensors

Pressure measurement is of great importance due to its wide range of applications in many fields. AT-cut quartz, with its exceptional precision and durability, stands out as an excellent pressure transducer due to its superior accuracy and stable performance over time. However, its intrinsic temperature dependence significantly hinders its potential application in varying temperature environments. Herein, three different learning algorithms (i.e., multivariate polynomial regression, multilayer perceptron networks, and support vector regression) are elaborated in detail and applied to establish the prediction models for compensating the temperature effect of the resonant pressure sensor, respectively. The AC-cut quartz, which is sensitive to temperature variations, is paired with the AT-cut quartz, providing the essential temperature information. The output frequencies derived from the AT-cut and AC-cut quartzes are selected as input data for these learning algorithms. Through experimental validation, all three methods are effective, and a remarkable improvement in accuracy can be achieved. Among the three methods, the MPR model has exceptionally high accuracy in predicting pressure. The calculated residual error over the temperature range of -10-40 °C is less than 0.008% of 40 MPa full scale (FS). An intelligent automatic compensation and real-time processing system for the resonant pressure sensor is developed as well, which may contribute to improving the efficiency in online calibration and large-scale industrialization. This paper paves a promising way for the temperature compensation of resonant pressure sensors.

Research on the Mechanical Properties and Temperature Compensation of an Intelligent Pot Bearing for a Pipe-Type Welding Strain Gauge

As an important component connecting the upper and lower structures of a bridge, bridge bearings can reliably transfer vertical and horizontal loads to a foundation. Bearing capacity needs to be monitored during construction and maintenance. To create an intelligent pot bearing, a portable small spot welding machine is used to weld pipe-type welding strain gauges to the pot bearing to measure strain and force values. The research contents of this paper include the finite element analysis of a basin bearing, optimal arrangement of welding strain gauges, calibration testing, and temperature compensation testing of the intelligent basin bearing of the welding strain gauges. Polynomial fitting is used for the fitting and analysis of test data. The results indicate that the developed intelligent pot bearing has a high-precision force measurement function and that after temperature compensation, the measurement error is within 1.8%. The intelligent pot bearing has a low production cost, and the pipe-type welding strain gauges can be conveniently replaced. The novelty is that the bearing adopts a robust pipe-type welding strain gauge and that automatic temperature compensation is used. Therefore, the research results have excellent engineering application value.

Temperature Compensation of SAW Winding Tension Sensor Based on PSO-LSSVM Algorithm

In this paper, a SAW winding tension sensor is designed and data fusion technology is used to improve its measurement accuracy. To design a high-measurement precision SAW winding tension sensor, the unbalanced split-electrode interdigital transducers (IDTs) were used to design the input IDTs and output IDTs, and the electrode-overlap envelope was adopted to design the input IDT. To improve the measurement accuracy of the sensor, the particle swarm optimization-least squares support vector machine (PSO-LSSVM) algorithm was used to compensate for the temperature error. After temperature compensation, the sensitivity temperature coefficient αs of the SAW winding tension sensor was decreased by an order of magnitude, thus significantly improving its measurement accuracy. Finally, the error with actually applied tension was calculated, the same in the LSSVM and PSO-LSSVM. By multiple comparisons of the same sample data set overall, as well as the local accuracy of the forecasted results, which is 5.95%, it is easy to confirm that the output error predicted by the PSO-LSSVM model is 0.50%, much smaller relative to the LSSVM's 1.42%. As a result, a new way for performing data analysis of the SAW winding tension sensor is provided.

Temperature Drift Compensation of Fiber Optic Gyroscopes Based on an Improved Method

This study proposes an improved multi-scale permutation entropy complete ensemble empirical mode decomposition with adaptive noise (MPE-CEEMDAN) method based on adaptive Kalman filter (AKF) and grey wolf optimizer-least squares support vector machine (GWO-LSSVM). By establishing a temperature compensation model, the gyro temperature output signal is optimized and reconstructed, and a gyro output signal is obtained with better accuracy. Firstly, MPE-CEEMDAN is used to decompose the FOG output signal into several intrinsic mode functions (IMFs); then, the IMFs signal is divided into mixed noise, temperature drift, and other noise according to different frequencies. Secondly, the AKF method is used to denoise the mixed noise. Thirdly, in order to denoise the temperature drift, the fiber gyroscope temperature compensation model is established based on GWO-LSSVM, and the signal without temperature drift is obtained. Finally, the processed mixed noise, the processed temperature drift, the processed other noise, and the signal-dominated IMFs are reconstructed to acquire the improved output signal. The experimental results show that, by using the improved method, the output of a fiber optic gyroscope (FOG) ranging from -30 °C to 60 °C decreases, and the temperature drift dramatically declines. The factor of quantization noise (Q) reduces from 6.1269 × 10-3 to 1.0132 × 10-4, the factor of bias instability (B) reduces from 1.53 × 10-2 to 1 × 10-3, and the factor of random walk of angular velocity (N) reduces from 7.8034 × 10-4 to 7.2110 × 10-6. The improved algorithm can be adopted to denoise the output signal of the FOG with higher accuracy.

A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber

In this paper, we propose a novel shape-sensing method based on deep learning with a multi-core optical fiber for the accurate shape-sensing of catheters and guidewires. Firstly, we designed a catheter with embedded multi-core fiber containing three sensing outer cores and one temperature compensation middle core. Then, we analyzed the relationship between the central wavelength shift, the curvature of the multi-core Fiber Bragg Grating (FBG), and temperature compensation methods to establish a Particle Swarm Optimization (PSO) BP neural network-based catheter shape sensing method. Finally, experiments were conducted in both constant and variable temperature environments to validate the method. The average and maximum distance errors of the PSO-BP neural network were 0.57 and 1.33 mm, respectively, under constant temperature conditions, and 0.36 and 0.96 mm, respectively, under variable temperature conditions. This well-sensed catheter shape demonstrates the effectiveness of the shape-sensing method proposed in this paper and its potential applications in real surgical catheters and guidewire.

Combined Temperature Compensation Method for Closed-Loop Microelectromechanical System Capacitive Accelerometer

This article describes a closed-loop detection MEMS accelerometer for acceleration measurement. This paper analyzes the working principle of MEMS accelerometers in detail and explains the relationship between the accelerometer zero bias, scale factor and voltage reference. Therefore, a combined compensation method is designed via reference voltage source compensation and terminal temperature compensation of the accelerometer, which comprehensively improves the performance over a wide temperature range of the accelerometer. The experiment results show that the initial range is reduced from 3679 ppm to 221 ppm with reference voltage source compensation, zero-bias stability of the accelerometer over temperature is increased by 14.3% on average and the scale factor stability over temperature is increased by 88.2% on average. After combined compensation, one accelerometer zero-bias stability over temperature was reduced to 40 μg and the scale factor stability over temperature was reduced to 16 ppm, the average value of the zero-bias stability over temperature was reduced from 1764 μg to 36 μg, the average value of the scale factor stability over temperature was reduced from 2270 ppm to 25 ppm, the average stability of the zero bias was increased by 97.96% and the average stability of the scale factor was increased by 98.90%.

Temperature Compensation of Wind Tunnel Balance Signal Detection System Based on IGWO-ELM

The wind tunnel balance signal detection system is widely employed in aerospace applications for the accurate and automated measurement of aerodynamic forces and moments. However, measurement errors arise under different environmental temperature. This paper addresses the issue of measurement accuracy under different temperature conditions by proposing a temperature compensation method based on an improved gray wolf optimization (IGWO) algorithm and optimized extreme learning machine (ELM). The IGWO algorithm is enhanced by improving the initial population position, convergence factor, and iteration weights of the gray wolf optimization algorithm. Subsequently, the IGWO algorithm is employed to determine the optimal network parameters for the ELM. The calibration decoupling experiment and high-low temperature experiment are designed and carried out. On this basis, ELM, GWO-ELM, PSO-ELM, GWO-RBFNN and IGWO-ELM are used for temperature compensation experiments. The experimental results show that IGWO-ELM has a good temperature compensation effect, reducing the measurement error from 20%FS to within 0.04%FS. Consequently, the accuracy and stability of the wind tunnel balance signal detection system under different temperature environments are enhanced.

Fabrication of Temperature- and Humidity-Independent Silver Nanoparticle's Carbon Composite-Based Strain Sensor Through Additive Manufacturing Process

A highly sensitive low-cost strain sensor was fabricated in this research study based on microdispensing direct write (MDDW) technique. MDDW is an additive manufacturing approach that involves direct deposition of functional material to the substrate. The devices were printed directly onto a polymeric substrate by optimizing the fabrication parameters. A composite of silver and carbon was used as active sensor material where both materials in the composite have opposite resistance temperature coefficients. The ratio of materials in the composite was selected so that the effect of temperature on the resistance of overall composite was canceled out. This resulted in achieving temperature compensation or inherent independence of the strain sensor resistance on temperature without requiring any additional sensors and components. The sensor was further encapsulated by electrospray deposition, which is also an additive manufacturing approach, to eliminate the effect of humidity as well. Electrical and morphological characterizations were performed to investigate the output response of the sensors and their physical and structural properties. An analog signal conditioning circuit was developed for seamless interfacing of the sensor with any electronic system. The sensor had an excellent gauge factor of 45 and a strain sensitivity of 45 Ω/μɛ that is higher than most of the conventional strain sensors. The sensor's response showed excellent temperature and humidity compensation reducing the relative effect of temperature on the resistance by ∼99.5% and humidity by ∼99.8%.

Temperature-Independent Sensor of the Magnetic Field Based on FBG and Terfenol-D

Sensors based on Fiber Bragg Grating (FBG) have remarkable benefits like small size, fast response, wide sensing distribution, and immunity to electromagnetic interference, allowing for their widespread application in numerous domains of physical parameter measurement in industrial engineering. In this work, a temperature-independent sensor of the magnetic field based on FBG and the magnetostrictive material Terfenol-D is suggested. By exploiting the distributed sensing characteristic of FBG, a sensing structure that remains unaffected by temperature is designed. The results demonstrate that within the magnetic induction intensity range of 0 mT to 50 mT, the sensitivity of the sensor can reach 7.382 pm/mT, exhibiting good linearity and repeatability. Compared with the control experiment and other sensors of the magnetic field containing Terfenol-D, the sensor has higher sensitivity, better repeatability, and good temperature stability.

Embedded Fiber Bragg Grating Sensors for Monitoring Temperature and Thermo-Elastic Deformations in a Carbon Fiber Optical Bench

A composite optical bench made up of Carbon Fiber Reinforced Polymer (CFRP) skin and aluminum honeycomb has been developed for the Tunable Magnetograph instrument (TuMag) for the SUNRISE III mission within the NASA Long Duration Balloon Program. This optical bench has been designed to meet lightweight and low sensitivity to thermal gradient requirements, resulting in a low Coefficient of Thermal Expansion (CTE). In addition to the flight model, a breadboard model identical to the flight one has been manufactured, including embedded fiber Bragg temperature and strain sensors. The aim of this is to explore if the use of distributed fiber Bragg gratings (FBGs) can provide valuable information for strain and temperature mapping of an optical instrument on board a space mission during its operation as well as its on-ground testing. Furthermore, surface-mounted strain FBG sensors and thermocouples have been installed in the optical bench for intercomparison purposes. This paper presents the results obtained from a thermal vacuum test consisting of three thermal cycles with stabilization steps at 100 °C, 60 °C, 20 °C and -20 °C. Experimental results provide information about how FBG embedded temperature sensors can provide a proper and quick response to the temperature changes of the optical bench and that embedded FBG strain sensors are able to measure micro-deformation induced in a close-to-zero CTE optical bench.

A 254-nW 20-kHz On-Chip RC Oscillator With 21-ppm/°C Minimum Temperature Stability and 10-ppm Long Term Stability

This paper presents a temperature compensated RC oscillator (TC-RCO) designed in 130 nm CMOS technology using regular VTH transistors. The TC-RCO uses constant transconductance gm biasing for first order temperature compensation. Device mismatch based offset correction and delay compensation techniques in the comparator are used to improve temperature instability by cancelling out second order effects. The oscillator achieves a minimum temperature stability down to 21 ppm/°C for a temperature range of -20 to 100 °C. In the lowest power mode, the oscillator consumes 254 nW power with a 1 V supply. The TC-RCO is operated in two modes, a low power mode that consumes an average of 254 nW and a high stability mode that consumes an average of 345 nW. A duty-cycling technique is used to correct offset after four cycles of oscillation. The oscillator exhibits long term stability of 10 ppm after 1 s integration time.

Temperature compensation and entrainment in cyanobacteria circadian rhythm

Circadian rhythm is an endogenous rhythmic behavior of organisms used to adapt to the external environment. Although most biochemical reactions accelerate with increasing temperature, the period of circadian rhythms remains relatively stable across a range of temperature, a phenomenon known as temperature compensation. Meanwhile, circadian rhythms can be reset by environmental signals, such as daily periodic light or temperature, a phenomenon known as entrainment. Cyanobacteria are the simplest organisms to have circadian rhythms. The effect of light on cyanobacteria circadian rhythm has been widely studied with mathematical models. However, the effect of temperature on cyanobacteria circadian rhythm and the mechanisms of temperature compensation and entrainment are far from clear. In this paper, we apply a recent model to incorporate temperature dependence by Van't Hoff rule. With numerical simulation, we study the temperature compensation and entrainment in detail. The results show that the system can exhibit temperature compensation when the post-transcription process is insensitive to temperature. The temperature compensation is caused by the cancellation of the increase of amplitude and the acceleration of speed, resulting in the stable period, when the temperature rises. The system can also exhibit temperature entrainment in constant light in a very limited temperature range. When the periodic light is added simultaneously to simulate more realistic environment, the temperature range of entrainment is greatly improved. The results also suggest that long-day condition is conducive to entrainment. The findings of this paper provide a theoretical reference for biological research and help us understand the dynamical mechanisms of cyanobacteria circadian rhythm.

Accurate Cutting-Force Measurement with Smart Tool Holder in Lathe

Cutting force in lathe work is closely related to tool wear and affects the turning quality. Direct measurement of the cutting force by measuring the strain of the tool holder is challenging because the tool holder design aims to be highly rigid in order to undertake large cutting forces. Accordingly, the most popular dynamometer designs modify the standard tool holder by decreasing the structural rigidity of the holder, which reduces the machining precision and is not widely accepted. In order to solve the issue of the low stiffness of the dynamometer reducing the machining precision, in this paper, the ultra-low strain on the tool holder was successfully detected by the highly sensitive semiconductor strain gauges (SCSG) adjacent to the blade cutting insert. However, the cutting process would generate much heat, which increases the force measuring area temperature of the tool holder by about 30 °C. As a result, the readout drifted significantly with the temperature changes due to the high temperature coefficient of SCSG. To solve this problem, the temperature on the tool holder was monitored and a BP neural network was proposed to compensate for temperature drift errors. Our methods improved the sensitivity (1.14 × 10^-2 mV/N) and the average relative error of the BP neural network prediction (≤1.48%) while maintaining the original stiffness of the tool holder. The smart tool holder developed possesses high natural frequency (≥6 kHz), it is very suitable for dynamic cutting-force measurement. The cutting experiment data in the lathe work show comparable performance with the traditional dynamometers and the resolution of the smart tool holder is 2 N (0.25% of total range).

Development and Temperature Correction of Piezoelectric Ceramic Sensor for Traffic Weighing-In-Motion

Weighing-In-Motion (WIM) technology is one of the main tools for pavement management. It can accurately describe the traffic situation on the road and minimize overload problems. WIM sensors are the core elements of the WIM system. The excellent basic performance of WIMs sensor and its ability to maintain a stable output under different temperature environments are critical to the entire process of WIM. In this study, a WIM sensor was developed, which adopted a PZT-5H piezoelectric ceramic and integrated a temperature probe into the sensor. The designed WIM sensor has the advantages of having a small size, simple structure, high sensitivity, and low cost. A sine loading test was designed to test the basic performance of the piezoelectric sensor by using amplitude scanning and frequency scanning. The test results indicated that the piezoelectric sensor exhibits a clear linear relationship between input load and output voltage under constant environmental temperature. The linear correlation coefficient R² of the fitting line is up to 0.999, and the sensitivity is 4.04858 mV/N at a loading frequency of 2 Hz at room temperature. The sensor has good frequency-independent characteristics. However, the temperature has a significant impact on it. Therefore, the output performance of the piezoelectric ceramic sensor is stabilized under different temperature conditions by using a multivariate nonlinear fitting algorithm for temperature compensation. The fitting result R² is 0.9686, the root mean square error (RMSE) is 0.2497, and temperature correction was achieved. This study has significant implications for the application of piezoelectric ceramic sensors in road WIM systems.

Compact Back-End Electronics with Temperature Compensation and Efficient Data Management for In Situ SiPM-Based Radiation Detection

A compact back-end interface for silicon photomultipliers (SiPMs) implementing Zener diode-based temperature compensation has been developed for the remote detection of beta and gamma radiation. Remote detection is facilitated by the development of an efficient data management system utilising MySQL database storage for recording periodic spectra data for wireless access over a private Wi-Fi network. A trapezoidal peak shaping algorithm has been implemented on an FPGA for the continuous conversation of pulses from the SiPM, signifying the detection of a radiological particle, into spectra. This system has been designed to fit within a 46 mm cylindrical diameter for in situ characterization, and can be attached to one or more SiPMs used in conjunction with a range of scintillators. LED blink tests have been used to optimise the trapezoidal shaper coefficients to maximise the resolution of the recorded spectra. Experiments with an array of SiPMs integrated with a NaI(Tl) scintillator exposed to sealed sources of Co-60, Cs-137, Na-22 and Am-241 have shown that the detector achieves a peak efficiency of 27.09 ± 0.13% for a gamma peak at 59.54 keV produced by Am-241, and a minimum energy resolution (Delta E/E) of 4.27 ± 1.16% for the 1332.5 keV gamma peak from Co-60.

Limits of the thermal tolerance of two lentic crustaceans: The role of lactate dehydrogenase

Limits of thermal tolerance in animal life is dependent on energy supply. Accordingly, the lowered ATP production capacity in ectotherms at high temperatures, which arises from a mismatch between oxygen supply and demand and the consequent switch from aerobic to anaerobic metabolism, affects the thermal resistance of these animals. The anaerobic ATP production capacity depends on the functional properties of the enzymes that reduce pyruvate. Thus, the present study focused on the role of the lactate dehydrogenase (LDH) of two daphnid species for anaerobic energy production at warm temperatures and the implications for their specific heat tolerances. Daphnia magna showed a higher thermal limit (indicated by immobilization time at 37°C) than Daphnia pulex, and in both species, this limit increased with rising acclimation temperature. In contrast to D. pulex, D. magna accumulated significant amounts of lactate at higher ambient temperatures. The intensity of anaerobic metabolism was also affected by acclimation temperature. Studying the functional enzyme properties revealed altered maximal reaction rates and substrate inhibitions of the LDH suites of the two daphnid species. D. magna LDH showed a significantly lower substrate inhibition than D. pulex LDH. The LDH isoform composition and the temperature-induced changes differed between both species. The detected qualitative modulations of the LDH suites may have resulted from differential isoform expression and different maturation processes. The species-specific LDH characteristics imply a higher anaerobic energy production at warm temperatures in D. magna, which likely contributes to the higher heat tolerance of this species.

Optical Fiber Fabry-Pérot Microfluidic Sensor Based on Capillary Fiber and Side Illumination Method

In this paper, an optical fiber Fabry-Pérot (FP) microfluidic sensor based on the capillary fiber (CF) and side illumination method is designed. The hybrid FP cavity (HFP) is naturally formed by the inner air hole and silica wall of CF which is side illuminated by another single mode fiber (SMF). The CF acts as a naturally microfluidic channel, which can be served as a potential microfluidic solution concentration sensor. Moreover, the FP cavity formed by silica wall is insensitive to ambient solution refractive index but sensitive to the temperature. Thus, the HFP sensor can simultaneously measure microfluidic refractive index (RI) and temperature by cross-sensitivity matrix method. Three sensors with different inner air hole diameters were selected to fabricate and characterize the sensing performance. The interference spectra corresponding to each cavity length can be separated from each amplitude peak in the FFT spectra with a proper bandpass filter. Experimental results indicate that the proposed sensor with excellent sensing performance of temperature compensation is low-cost and easy to build, which is suitable for in situ monitoring and high-precision sensing of drug concentration and the optical constants of micro-specimens in the biomedical and biochemical fields.

A Novel Catheter Distal Contact Force Sensing for Cardiac Ablation Based on Fiber Bragg Grating with Temperature Compensation

OBJECTIVE

To accurately achieve distal contact force, a novel temperature-compensated sensor is developed and integrated into an atrial fibrillation (AF) ablation catheter.

METHODS

A dual elastomer-based dual FBGs structure is used to differentiate the strain on the two FBGs to achieve temperature compensation, and the design is optimized and validated by finite element simulation.

RESULTS

The designed sensor has a sensitivity of 90.5 pm/N, resolution of 0.01 N, and root-mean-square error (RMSE) of 0.02 N and 0.04 N for dynamic force loading and temperature compensation, respectively, and can stably measure distal contact forces with temperature disturbances.

CONCLUSION

Due to the advantages, i.e., simple structure, easy assembly, low cost, and good robustness, the proposed sensor is suitable for industrial mass production.

Thermal Calibration of Triaxial Accelerometer for Tilt Measurement

The application of MEMS accelerometers used to measure inclination is constrained by their temperature dependence, and each accelerometer needs to be calibrated individually to increase stability and accuracy. This paper presents a calibration and thermal compensation method for triaxial accelerometers that aims to minimize cost and processing time while maintaining high accuracy. First, the number of positions to perform the calibration procedure is optimized based on the Levenberg-Marquardt algorithm, and then, based on this optimized calibration number, thermal compensation is performed based on the least squares method, which is necessary for environments with large temperature variations, since calibration parameters change at different temperatures. The calibration procedures and algorithms were experimentally validated on marketed accelerometers. Based on the optimized calibration method, the calibrated results achieved nearly 100 times improvement. Thermal drift calibration experiments on the triaxial accelerometer show that the thermal compensation scheme in this paper can effectively reduce drift in the temperature range of -40 °C to 60 °C. The temperature drifts of x- and y-axes are reduced from -13.2 and 11.8 mg to -0.9 and -1.1 mg, respectively. The z-axis temperature drift is reduced from -17.9 to 1.8 mg. We have conducted various experiments on the proposed calibration method and demonstrated its capacity to calibrate the sensor frame error model (SFEM) parameters. This research proposes a new low-cost and efficient strategy for increasing the practical applicability of triaxial accelerometers.

Functional analysis of 110 phosphorylation sites on the circadian clock protein FRQ identifies clusters determining period length and temperature compensation

In the negative feedback loop driving the Neurospora circadian oscillator, the negative element, FREQUENCY (FRQ), inhibits its own expression by promoting phosphorylation of its heterodimeric transcriptional activators, White Collar-1 (WC-1) and WC-2. FRQ itself also undergoes extensive time-of-day-specific phosphorylation with over 100 phosphosites previously documented. Although disrupting individual or certain clusters of phosphorylation sites has been shown to alter circadian period lengths to some extent, it is still elusive how all the phosphorylations on FRQ control its activity. In this study, we systematically investigated the role in period determination of all 110 reported FRQ phosphorylation sites, using mutagenesis and luciferase reporter assays. Surprisingly, robust FRQ phosphorylation is still detected even when 84 phosphosites were eliminated altogether; further mutating another 26 phosphoresidues completely abolished FRQ phosphorylation. To identify phosphoresidue(s) on FRQ impacting circadian period length, a series of clustered frq phosphomutants covering all the 110 phosphosites were generated and examined for period changes. When phosphosites in the N-terminal and middle regions of FRQ were eliminated, longer periods were typically seen while removal of phosphorylation in the C-terminal tail resulted in extremely short periods, among the shortest reported. Interestingly, abolishing the 11 phosphosites in the C-terminal tail of FRQ not only results in an extremely short period, but also impacts temperature compensation (TC), yielding an overcompensated circadian oscillator. In addition, the few phosphosites in the middle of FRQ are also found to be crucial for TC. When different groups of FRQ phosphomutations were combined intramolecularly, expected additive effects were generally observed except for one novel case of intramolecular epistasis, where arrhythmicity resulting from one cluster of phosphorylation site mutants was restored by eliminating phosphorylation at another group of sites.

Temperature Compensation for Reusable Piezo Configuration for Condition Monitoring of Metallic Structures: EMI Approach

This paper presents a novel algorithm for compensating the changes in conductance signatures of a piezo sensor due to the temperature variation employed in condition monitoring using the electro-mechanical impedance (EMI) approach. It is crucial to consider the changes in an EMI signature due to temperature before using it for comparison with the baseline signature. The shifts in the signature due to temperature can be misinterpreted as damages to the structure, which might also result in a false alarm. In the present study, the compensation values are calculated based on experiments on piezo sensors both in a free boundary condition and in a bonded condition on a metallic host structure. The values were further validated experimentally for damage detection on a large 2D steel plate structure. The variation in first natural frequency values for the unbonded piezo sensor at different temperatures has been used to develop the compensation algorithms. Whereas, in the case of the bonded sensor, the shift in structural peaks has been used. The developed compensation relations showed promising results in damage detection. Lastly, a finite element-based study has also been performed, supporting the experimental findings. The outcome of this study will aid in the compensation of the signatures in the structure due to temperature variation in the conductance signature.

A novel period mutation implicating nuclear export in temperature compensation of the Drosophila circadian clock

Circadian clocks are self-sustained molecular oscillators controlling daily changes of behavioral activity and physiology. For functional reliability and precision, the frequency of these molecular oscillations must be stable at different environmental temperatures, known as "temperature compensation." Despite being an intrinsic property of all circadian clocks, this phenomenon is not well understood at the molecular level. Here, we use behavioral and molecular approaches to characterize a novel mutation in the period (per) clock gene of Drosophila melanogaster, which alters a predicted nuclear export signal (NES) of the PER protein and affects temperature compensation. We show that this new per^I530A allele leads to progressively longer behavioral periods and clock oscillations with increasing temperature in both clock neurons and peripheral clock cells. While the mutant PER^I530A protein shows normal circadian fluctuations and post-translational modifications at cool temperatures, increasing temperatures lead to both severe amplitude dampening and hypophosphorylation of PER^I530A. We further show that PER^I530A displays reduced repressor activity at warmer temperatures, presumably because it cannot inactivate the transcription factor CLOCK (CLK), indicated by temperature-dependent altered CLK post-translational modification in per^I530A flies. With increasing temperatures, nuclear accumulation of PER^I530A within clock neurons is increased, suggesting that wild-type PER is exported out of the nucleus at warm temperatures. Downregulating the nuclear export factor CRM1 also leads to temperature-dependent changes of behavioral rhythms, suggesting that the PER NES and the nuclear export of clock proteins play an important role in temperature compensation of the Drosophila circadian clock.

Bias-Repeatability Analysis of Vacuum-Packaged 3-Axis MEMS Gyroscope Using Oven-Controlled System

The performance of microelectromechanical system (MEMS) inertial measurement units (IMUs) is susceptible to many environmental factors. Among different factors, temperature is one of the most challenging issues. This report reveals the bias stability analysis of an ovenized MEMS gyroscope. A micro-heater and a control system exploiting PID/PWM were used to compensate for the bias stability variations of a commercial MEMS IMU from BOSCH "BMI 088". A micro-heater made of gold (Au) thin film is integrated with the commercial MEMS IMU chip. A custom-designed micro-machined glass platform thermally isolates the MEMS IMU from the ambient environment and is vacuum sealed in the leadless chip carrier (LCC) package. The BMI 088 built-in temperature sensor is used for temperature sensing of the device and the locally integrated heater. The experimental results reveal that the bias repeatability of the devices has been improved significantly to achieve the target specifications, making the commercial devices suitable for navigation. Furthermore, the effect of vacuum-packaged and non-vacuum-packaged devices was compared. It was found that the bias repeatability of vacuum-packaged devices was improved by more than 60%.

Interrogation Method with Temperature Compensation Using Ultra-Short Fiber Bragg Gratings in Silica and Polymer Optical Fibers as Edge Filters

The use of simpler and less bulky equipment, with a reliable performance and at relative low cost is increasingly important when assembling sensing configurations for a wide variety of applications. Based on this concept, this paper proposes a simple, efficient and relative low-cost fiber Bragg grating (FBG) interrogation solution using ultra-short FBGs (USFBGs) as edge filters. USFBGs with different lengths and reflection bandwidths were produced in silica optical fiber and in poly(methyl methacrylate) (PMMA) microstructured polymer optical fiber (mPOF), and by adjusting specific inscription parameters and the diffraction pattern, these gratings can present self-apodization and unique spectral characteristics suitable for filtering operations. In addition to being a cost-effective edge filter solution, USFBGs and standard uniform FBGs in silica fiber have similar thermal sensitivities, which results in a straightforward operation without complex equipment or calculations. This FBG interrogation configuration is also quite promising for dynamic measurements, and due to its multiplexing capabilities multiple USFBGs can be inscribed in the same optical fiber, allowing to incorporate several filters with identical or different spectral characteristics at specific wavelength regions in the same fiber, thus showing great potential to create and develop new sensing configurations.

Evolution of casein kinase 1 and functional analysis of new doubletime mutants in Drosophila

Circadian clocks are timing devices that rhythmically adjust organism's behavior, physiology, and metabolism to the 24-h day-night cycle. Eukaryotic circadian clocks rely on several interlocked transcription-translation feedback loops, where protein stability is the key part of the delay between transcription and the appearance of the mature proteins within the feedback loops. In bilaterian animals, including mammals and insects, the circadian clock depends on a homologous set of proteins. Despite mostly conserved clock components among the fruit fly Drosophila and mammals, several lineage-specific differences exist. Here we have systematically explored the evolution and sequence variability of insect DBT proteins and their vertebrate homologs casein kinase 1 delta (CKIδ) and epsilon (CKIε), dated the origin and separation of CKIδ from CKIε, and identified at least three additional independent duplications of the CKIδ/ε gene in Petromyzon, Danio, and Xenopus. We determined conserved regions in DBT specific to Diptera, and functionally tested a subset of those in D. melanogaster. Replacement of Lysine K224 with acidic residues strongly impacts the free-running period even in heterozygous flies, whereas homozygous mutants are not viable. K224D mutants have a temperature compensation defect with longer free-running periods at higher temperatures, which is exactly the opposite trend of what was reported for corresponding mammalian mutants. All DBTs of dipteran insects contain the NKRQK motif at positions 220-224. The occurrence of this motif perfectly correlates with the presence of BRIDE OF DOUBLETIME, BDBT, in Diptera. BDBT is a non-canonical FK506-binding protein that physically interacts with Drosophila DBT. The phylogeny of FK506-binding proteins suggests that BDBT is either absent or highly modified in non-dipteran insects. In addition to in silico analysis of DBT/CKIδ/ε evolution and diversity, we have identified four novel casein kinase 1 genes specific to the Drosophila genus.

Accurate Flow Characterization of A6082 for Precision Simulation of a Hot Metal Forming Process

The flow behaviors of metallic materials are sensitive to state variables, including strain, strain rate, and temperature. In particular, the temperature effect on the flow behavior is of great importance. The flow information is usually obtained at the sample strain rates and temperatures from the hot cylinder compression test. However, this test is inevitably exposed to undesirable effects of friction and temperature on flow characterization. This study reveals their impact on the flow curve of an A6082 alloy. The unique features of its flow behavior and the inaccuracy of as-received, primitive flow information are emphasized. Using a systematic way of correcting the friction and temperature effects, the flow curves with high accuracy in terms of the compression load-stroke curve obtained from the test are calculated. It was revealed that the both the friction and temperature compensation of the primitive flow curves bring a minor change in the flow curves of the A6082 alloy, which is quite different from other commercial light metals. This phenomenon caused by the unique features of the flow behavior of the A6082 or other aluminum alloys will be critical to solving various process and quality matters confronted by the engineers in the hot metal forming industry.

Design of Precision-Aware Subthreshold-Based MOSFET Voltage Reference

A new precision-aware subthreshold-based MOSFET voltage reference is presented in this paper. The circuit was implemented TSMC-40 nm process technology. It consumed 9.6 μW at the supply voltage of 1.2 V. In this proposed work, by utilizing subthreshold-based MOSFET instead of bipolar junction transistor (BJT), relatively lower power consumption was obtained in the design while offering comparable precision to that offered by its BJT counterpart. Through the proposed second-order compensation, it achieved the temperature coefficient (T.C.) of 3.0 ppm/°C in the TT corner case and a 200-sample Monte-Carlo T.C. of 12.51 ppm/°C from -40 °C to 90 °C. This shows robust temperature insensitivity. The process sensitivity of Vref without and with trimming was 2.85% and 0.75%, respectively. The power supply rejection (PSR) was 71.65 dB at 100 Hz and 52.54 dB at 10 MHz. The Figure-of-Merit (FOM) for the total variation in output voltage was comparable with representative BJT circuits and better than subthreshold-based MOSFET circuits. Due to low T.C., low process sensitivity, and simplicity of the circuit architecture, the proposed work will be useful for sensor circuits with stringent requirements or other analog circuits that require high precision applications.

Improved VMD-ELM Algorithm for MEMS Gyroscope of Temperature Compensation Model Based on CNN-LSTM and PSO-SVM

The micro-electro-mechanical system (MEMS) gyroscope is a micro-mechanical gyroscope with low cost, small volume, and good reliability. The working principle of the MEMS gyroscope, which is achieved through Coriolis, is different from traditional gyroscopes. The MEMS gyroscope has been widely used in the fields of micro-inertia navigation systems, military, automotive, consumer electronics, mobile applications, robots, industrial, medical, and other fields in micro-inertia navigation systems because of its advantages of small volume, good performance, and low price. The material characteristics of the MEMS gyroscope is very significant for its data output, and the temperature determines its accuracy and limits its further application. In order to eliminate the effect of temperature, the MEMS gyroscope needs to be compensated to improve its accuracy. This study proposed an improved variational modal decomposition-extreme learning machine (VMD-ELM) algorithm based on convolutional neural networks-long short-term memory (CNN-LSTM) and particle swarm optimization-support vector machines (PSO-SVM). By establishing a temperature compensation model, the gyro temperature output signal is optimized and reconstructed, and the gyro output signal with better accuracy is obtained. The VMD algorithm separates the gyro output signal and divides the gyro output signal into low-frequency signals, mid-frequency signals, and high-frequency signals according to the different signal frequencies. Once again, the PSO-SVM model is constructed by the mid-frequency temperature signal to find the temperature error. Finally, the signal is reconstructed through the ELM neural network algorithm, and then, the gyro output signal after noise is obtained. Experimental results show that, by using the improved method, the output of the MEMS gyroscope ranging from -40 to 60 °C reduced, and the temperature drift dramatically declined. For example, the factor of quantization noise (Q) reduced from 1.2419 × 10^-4 to 1.0533 × 10^-6, the factor of bias instability (B) reduced from 0.0087 to 1.8772 × 10^-4, and the factor of random walk of angular velocity (N) reduced from 2.0978 × 10^-5 to 1.4985 × 10^-6. Furthermore, the output of the MEMS gyroscope ranging from 60 to -40 °C reduced. The factor of Q reduced from 2.9808 × 10^-4 to 2.4430 × 10^-6, the factor of B reduced from 0.0145 to 7.2426 × 10^-4, and the factor of N reduced from 4.5072 × 10^-5 to 1.0523 × 10^-5. The improved algorithm can be adopted to denoise the output signal of the MEMS gyroscope to improve its accuracy.

Machine Learning and Swarm Optimization Algorithm in Temperature Compensation of Pressure Sensors

The main temperature compensation method for MEMS piezoresistive pressure sensors is software compensation, which processes the sensor data using various algorithms to improve the output accuracy. However, there are few algorithms designed for sensors with specific ranges, most of which ignore the operating characteristics of the sensors themselves. In this paper, we propose three temperature compensation methods based on swarm optimization algorithms fused with machine learning for three different ranges of sensors and explore the partitioning ratio of the calibration dataset on Sensor A. The results show that different algorithms are suitable for pressure sensors of different ranges. An optimal compensation effect was achieved on Sensor A when the splitting ratio was 33.3%, where the zero-drift coefficient was 2.88 × 10^-7/°C and the sensitivity temperature coefficient was 4.52 × 10^-6/°C. The algorithms were compared with other algorithms in the literature to verify their superiority. The optimal segmentation ratio obtained from the experimental investigation is consistent with the sensor operating temperature interval and exhibits a strong innovation.

Design and Analysis of Small Size Eddy Current Displacement Sensor

A systematic method is employed for the design and analysis of a small size eddy current (EC) displacement sensor. Simulations are first performed to determine the optimal winding structure and dimensions of the sensor. A linear-fitting approach is then developed for converting the AC displacement signal of the sensor to a DC signal. Finally, a compensation method is proposed for mitigating the temperature drift of the EC sensor under different working temperatures. The experimental results show that the proposed sensor has a sensitivity of approximately 3 μm, a working temperature range of 25-55 °C, and a linearity of ±1.025%.

Acoustic Limescale Layer and Temperature Measurement in Ultrasonic Flow Meters

Guided acoustic waves are commonly used in domestic water meters to measure the flow rate. The accuracy of this measurement method is affected by factors such as variations in temperature and limescale deposition inside of the pipe. In this work, a new approach using signals from different sound propagation paths is used to determine these quantities and allow for subsequent compensation. This method evaluates the different propagation times of guided Lamb waves in flow measurement applications. A finite element method-based model is used to identify the calibration curves for the device under test. The simulated dependencies on temperature and layer thickness are validated by experimental data. Finally, a test on simulated data with varying temperatures and limescale depositions proves that this method can be used to separate both effects. Based on these values, a flow measurement correction scheme can be derived that provides an improved resolution of guided acoustic wave-based flow meters.

Utilizing the Intrinsic Mode of Weakly Coupled Resonators for Temperature Compensation

Accelerometers based on outputting amplitude ratios in weakly coupled resonators (WCRs) are attractive because their parametric sensitivity is higher by two or three orders of magnitudes than those based on outputting frequency. However, the impact of temperature on the coupler is a key factor in accelerometer applications. This paper proposed a novel mode-localized WCR accelerometer with a temperature compensation mechanism, with sensitive elements incorporating a double-ended tuning fork (DETF) resonator, clamped-clamped (CC) resonator, and a micro-lever coupler. The DETF out-of-phase mode is utilized, which is only sensitive to temperature, to measure the temperature change of WCRs and complete the temperature compensation using the compensation algorithm. This proposed method has no time delay in measuring the temperature of sensitive elements and no temperature difference caused by the uneven temperature field. The parametric sensitivity in amplitude ratio (AR) to acceleration drifting with temperature was theoretically analyzed, and the novel device was designed and fabricated by a silicon-on-glass process. Both simulation and experiment results demonstrated that the coupling stiffness drifted with temperature, which resulted in the drifts of its sensitivity to acceleration and zero-bias stability. Using the intrinsic mode of WCRs, in terms of the DETF out-of-phase mode, as an in situ thermometer and carrying out the temperature compensation algorithm, the drift of zero bias could be suppressed from 102 mg to 4.5 mg (g is the gravity acceleration), and the drift of the parameter sensitivity in AR was suppressed from 0.74 AR/g to 0.02 AR/g with the temperature range from 330 K to 370 K and acceleration range from 0 g to 0.2 g.

Simulation of a Temperature-Compensated Voltage Sensor Based on Photonic Crystal Fiber Infiltrated with Liquid Crystal and Ethanol

A simulated design for a temperature-compensated voltage sensor based on photonic crystal fiber (PCF) infiltrated with liquid crystal and ethanol is presented in this paper. The holes distributed across the transverse section of the PCF provide two channels for mode coupling between the liquid crystal or ethanol and the fiber core. The couplings are both calculated accurately and explored theoretically using the finite element method (FEM). The influence of voltage on the alignment of the liquid crystal molecules and confinement loss of the fiber mode are studied. Liquid crystal molecules rotate which changes its properties as the voltage changes. As the characteristics of the liquid crystal will be affected by temperature, therefore, we further fill using ethanol, which is merely sensitive to temperature, into one hole of the PCF to realize temperature compensation. The simulated results show that the sensitivity is up to 1.29977 nm/V with the temperature of 25 °C when the voltage ranges from 365 to 565 V. The standard deviation of the wavelength difference is less than 2 nm within the temperature adjustment from 25 to 50 °C for temperature compensation. The impacts of the construction parameters of the PCF on sensing performances of this voltage sensor are also analyzed in this paper.

Research on Temperature Compensation of Multi-Channel Pressure Scanner Based on an Improved Cuckoo Search Optimizing a BP Neural Network

A multi-channel pressure scanner is an essential tool for measuring and acquiring various pressure parameters in aerospace applications. It is important to note, however, that the pressure sensor of each of these channels will drift significantly with the increase in the temperature range of the pressure measurement, and the output voltage of each of these channels will show nonlinear characteristics, which will constrain the improvements in the accuracy of the measurement. In the regression fitting process, it is difficult to fit nonlinear data with the traditional least-squares method, which leaves pressure measurement accuracy unsatisfactory. A temperature compensation method based on an improved cuckoo search optimizing a BP neural network for a multi-channel pressure scanner is proposed in this paper to improve pressure measurement accuracy in a wide temperature range. Using the chaotic simplex algorithm, we first improved the cuckoo search algorithm, then optimized the connection weights and thresholds of the BP neural network, and finally constructed an experimental calibration system to investigate the temperature compensation of the multi-channel pressure scanning valves in the -40 °C to 60 °C temperature range. The compensation test results show that the algorithm has a better compensation effect and is more suitable for the temperature compensation of multi-channel pressure scanners than the traditional least-squares method and the standard RBF and BP neural networks. The maximum full-scale error of all 32 channels is 0.02% FS (full-scale error) and below, which realizes its high-accuracy multi-point pressure measurement in a wide temperature range.

Multiple Quartz Crystals Connected in Parallel for High-Resolution Sensing of Capacitance Changes

We present a new highly sensitive, low-value capacitance sensor method that uses multiple quartz crystals connected in parallel inside the oscillator. In the experimental setup, the measured (sensible) reactance (capacitance) is connected in parallel to the total shunt capacitance of the quartz crystals, oscillating in the oscillator. Because AT-cut crystals have a certain nonlinear frequency−temperature dependence, we use the switching mode method, by which we achieve a temperature compensation of the AT-cut crystals’ frequency−temperature characteristics in the temperature range between 0−50 °C. The oscillator switching method also compensates for any other influences on the frequency of the oscillator, such as ageing of the crystals and oscillator elements, supply voltage fluctuations, and other parasitic impedances in the oscillating circuit. Subsequently using two 50-ms-delayed switches between the measuring and reference capacitors, the experimental error in measuring the capacitance is lowered for measurements under a dynamic temperature variation in the range of 0−50 °C. The experimental results show that the switching method, which includes a multiple quartz connection and high-temperature compensation improvement of the quartz crystals’ characteristics, enables a sub-aF resolution. It converts capacitance changes in the range 10 zF−200 fF to frequencies in the range 4 kHz−100 kHz.

A Temperature Compensation Method for aSix-Axis Force/Torque Sensor Utilizing Ensemble hWOA-LSSVM Based on Improved Trimmed Bagging

The performance of a six-axis force/torque sensor (F/T sensor) severely decreased when working in an extreme environment due to its sensitivity to ambient temperature. This paper puts forward an ensemble temperature compensation method based on the whale optimization algorithm (WOA) tuning the least-square support vector machine (LSSVM) and trimmed bagging. To be specific, the stimulated annealing algorithm (SA) was hybridized to the WOA to solve the local entrapment problem, and an adaptive trimming strategy is proposed to obtain the optimal trim portion for the trimmed bagging. In addition, inverse quote error (invQE) and cross-validation are employed to estimate the fitness better in training process. The maximum absolute measurement error caused by temperature decreased from 3.34% to 3.9×10-3% of full scale after being compensated by the proposed method. The analyses of experiments illustrate the ensemble hWOA-LSSVM based on improved trimmed bagging improves the precision and stability of F/T sensors and possesses the strengths of local search ability and better adaptability.

PERIOD Phosphoclusters Control Temperature Compensation of the Drosophila Circadian Clock

Ambient temperature varies constantly. However, the period of circadian pacemakers is remarkably stable over a wide-range of ecologically- and physiologically-relevant temperatures, even though the kinetics of most biochemical reactions accelerates as temperature rises. This thermal buffering phenomenon, called temperature compensation, is a critical feature of circadian rhythms, but how it is achieved remains elusive. Here, we uncovered the important role played by the Drosophila PERIOD (PER) phosphodegron in temperature compensation. This phosphorylation hotspot is crucial for PER proteasomal degradation and is the functional homolog of mammalian PER2 S478 phosphodegron, which also impacts temperature compensation. Using CRISPR-Cas9, we introduced a series of mutations that altered three Serines of the PER phosphodegron. While all three Serine to Alanine substitutions lengthened period at all temperatures tested, temperature compensation was differentially affected. S44A and S45A substitutions caused undercompensation, while S47A resulted in overcompensation. These results thus reveal unexpected functional heterogeneity of phosphodegron residues in thermal compensation. Furthermore, mutations impairing phosphorylation of the per s phosphocluster showed undercompensation, consistent with its inhibitory role on S47 phosphorylation. We observed that S47A substitution caused increased accumulation of hyper-phosphorylated PER at warmer temperatures. This finding was corroborated by cell culture assays in which S47A slowed down phosphorylation-dependent PER degradation at high temperatures, causing PER degradation to be excessively temperature-compensated. Thus, our results point to a novel role of the PER phosphodegron in temperature compensation through temperature-dependent modulation of the abundance of hyper-phosphorylated PER. Our work reveals interesting mechanistic convergences and differences between mammalian and Drosophila temperature compensation of the circadian clock.

Temperature Compensation of Fiber Bragg Grating Sensors in Smart Strand

Compared to other types of sensors, fiber optic sensors have improved accuracy and durability. Recently, the Smart Strand was developed to maximize the advantages of fiber optic sensors for measuring the cable forces in prestressed concrete structures or cable-supported bridges. The Smart Strand has fiber Bragg gratings (FBGs) embedded in a core wire of the seven-wire strand. Similar to other sensors, the strain measured at an FBG is affected by temperature; therefore, the temperature effect that is not related to the mechanical strain should be compensated for or corrected in the long-term measurement subjected to temperature variation. However, a temperature compensation procedure for the FBG has yet to be established, and relevant studies have used different formulas for the compensation. Moreover, when the FBG sensors are packaged with a certain material-such as fiber reinforced polymer-for protection, it is important to consider the interaction between the FBG, packaging material, and host material during thermal behavior. Therefore, this study proposed a reasonable procedure for temperature compensation for the FBG sensors embedded in packaging material and host material. In particular, the thermal sensitivity of the Smart Strand was intensively investigated. The proposed theoretical formulas were validated through comparison with data obtained from various specimens in a temperature-controlled chamber. Finally, the procedure was applied to correct the data measured using the Smart Strands in a 20-m-long full-scale specimen for about a year, thus resulting in a realistic trend of the long-term prestressing force.

[Infrared Sensor ZTP-135SR and Its Application in Infrared Body Temperature Measurement]

Body temperature is an essential physiological parameter. Conducting non-contact, fast and accurate measurement of temperature is increasing important under the background of COVID-19. The study introduces an infrared temperature measurement system based on the thermopile infrared temperature sensor ZTP-135SR. Extracting original temperature date of sensor, post-amplification and filter processing have been performed to ensure accuracy of the system. In addition, the temperature data of environmental compensation which obtained by polynomial fitting is added to the system to further improve measurement accuracy.

Verification of Tensile Force Estimation Method for Temporary Steel Rods of FCM Bridges Based on Area of Magnetic Hysteresis Curve Using Embedded Elasto-Magnetic Sensor

The free cantilever method (FCM) is a bridge construction method in which the left and right segments are joined in sequence from a pier without using a bottom strut. To support the imbalance of the left and right moments during construction, temporary steel rods, upon which tensile force is applied that cannot be managed after construction, are embedded in the pier. If there is an excessive loss of tensile force applied to the steel rods, the segments can collapse owing to the unbalanced moment, which may cause personal and property damage. Therefore, it is essential to monitor the tensile force in the temporary steel rods to prevent such accidents. In this study, a tensile force estimation method for the temporary steel rods of an FCM bridge using embedded Elasto-Magnetic (EM) sensors was proposed. After the tensile force was applied to the steel rods, the change in tensile force was monitored according to the changing area of a magnetic hysteresis curve, as measured by the embedded EM sensors. To verify the field applicability of the proposed method, the EM sensors were installed in an FCM bridge pier under construction. The three sensors were installed in conjunction with a sheath tube, and the magnetic hysteresis curve was measured over nine months. Temperature data from the measurement period were used to compensate for the error due to daily temperature fluctuations. The estimated tensile force was consistent with an error range of ±4% when compared with the reference value measured by the load cell. Based on the results of this experiment, the applicability of the proposed method was demonstrated.

Insights from an ancient gymnosperm lineage: ambient temperature and light and the timing of thermogenesis in cycad cones

PREMISE

Although maintaining the appropriate mid-day timing of the diel thermogenic events of cones of the dioecious cycads Macrozamia lucida and M. macleayi is central to the survival of both plant and pollinator in this obligate pollination mutualism, the nature of the underlying mechanism remains obscure. We investigated whether it is under circadian control. Circadian mechanisms control the timing of many ecologically important processes in angiosperms, yet only a few gymnosperms have been studied in this regard.

METHODS

We subjected cones to different ambient temperature and lighting regimens (constant temperature and darkness; stepwise cool/warm ambient temperatures in constant darkness; stepwise dark/light exposures at constant temperature) to determine whether the resulting timing of their thermogenic events was consistent with circadian control.

RESULTS

Cones exposed to constant ambient temperature and darkness generated multiple temperature peaks endogenously, with an average interpeak-temperature period of 20.7 (±0.20) h that is temperature-compensated (Q₁₀  = 1.02). Exposure to 24-h ambient temperature cycles (12 h cool/12 h warm, constant darkness) yielded an interpeak-temperature period of 24.0 (±0.05) h, accurately and precisely replicating the ambient temperature period. Exposure to 24-h photo-cycles (12 h light/12 h dark, constant ambient temperature) yielded a shorter, more variable interpeak-temperature period of 23 (±0.23) h.

CONCLUSIONS

Our results indicate that cycad cone thermogenesis is under circadian clock control and differentially affected by ambient temperature and light cycles. Our data from cycads (an ancient gymnosperm lineage) adds to what little is known about circadian timing in gymnosperms, which have rarely been studied from the circadian perspective.

A CMOS PSR Enhancer with 87.3 mV PVT-Insensitive Dropout Voltage for Sensor Circuits

A new power supply rejection (PSR) based enhancer with small and stable dropout voltage is presented in this work. It is implemented using TSMC-40 nm process technology and powered by 1.2 V supply voltage. A number of circuit techniques are proposed in this work. These include the temperature compensation for Level-Shifted Flipped Voltage Follower (LSFVF) and the Complementary-To-Absolute Temperature (CTAT) current reference. The typical output voltage and dropout voltage of the enhancer is 1.1127 V and 87.3 mV, respectively. The Monte-Carlo simulation of this output voltage yields a mean T.C. of 29.4 ppm/°C from −20 °C and 80 °C. Besides, the dropout voltage has been verified with good immunity against Process, Temperature and Process (PVT) variation through the worst-case simulation. Consuming only 4.75 μA, the circuit can drive load up to 500 μA to yield additional PSR improvement of 36 dB and 20 dB of PSR at 1 Hz and 1 MHz, respectively for the sensor circuit of interest. This is demonstrated through the application of an enhancer on the instrumentation Differential Difference Amplifier (DDA) for sensing floating bridge sensor signal. The comparative Monte-Carlo simulation results on a respective DDA circuit have revealed that the process sensitivity of output voltage of this work has achieved 14 times reduction in transient metrics with respect to that of the conventional counterpart over the operation temperature range in typical operation condition. Due to simplicity without voltage reference and operational amplifier(s), low power and small consumption of supply voltage headroom, the proposed work is very useful for supply noise sensitive analog or sensor circuit applications.