Wide Measurement Range Research Articles

Intrusion event recognition method for distributed fibre optic sensing systems based on Siamese networks

ABSTRACT Due to its high sensitivity and wide measurement range, the distributed optical fibre sensing system has been widely used in long-distance infrastructure monitoring, where it detects vibration signals caused by external events and provides effective early warnings. Given the complexity and diversity of external intrusion events, traditional closed-set classification methods cannot effectively exclude unknown signals. Open-set recognition methods, on the other hand, involve complex model designs, requiring boundary Algorithms and often the inclusion of information related to unknown classes. In this paper, we combine a Siamese network with a residual network to recognise events in the distributed optical fibre sensing system. Through experiments, by comparing the similarity with data in the database, we not only ensure very high accuracy in closed-set classification but also effectively exclude unknown class signals. Experimental results show that our method successfully rejects unknown class data with a 92% success rate, while maintaining closed-set classification accuracy at an average of 99%. Our approach demonstrates excellent performance.

ACESSIBILIDADE À PESSOA COM DEFICIÊNCIA NOS CARTÓRIOS EXTRAJUDICIAIS

The aim of this article is to discuss the problem of the accessibility for the disabled in extrajudicial notary and registry offices. To fulfill this aim, the article firstly talks about the range of the concept of accessibility, its social relevance, the laws that rules this subject, and the challenges and difficulties faced by people with disabilities. On the other hand, this essay demonstrates that the extrajudicial notary and registry offices have a lot of responsibility towards the Brazilian society, not only because their attributions are public but also due to the relevance of their services – specially in the current moment in which there is a tendency of dejudicialization in Brazil. Therefore, considering the inevitable conclusion that the extrajudicial notary and registry offices must be accessible to people with all kinds of disabilities, the paper will examine the wide range of measures and cautions that these offices should take to achieve this purpose, based on some projects that already exist.

Wheatstone Bridge MEMS Hydrogen Sensor with ppb-Level Detection Limit Based on the Palladium-Gold Alloy.

On some occasions, such as new energy clinics, monitoring the trace hydrogen at the ppb level is necessary. The traditional resistive hydrogen sensors based on the Pd alloys are very difficult to realize such an extremely low detection limit. To achieve a detection limit at the ppb level and also ensure good stability, a MEMS hydrogen sensor was designed in a suspended Wheatstone bridge structure, with all four resistive arms defined on a sputtered Pd-Au alloy thin film. For the Wheatstone bridge sensor, absolute response (Ra) and relative response (Rs) are defined to describe the sensitivity of the sensor, and the effect of annealing temperature on baseline drift is investigated using the baseline zero drift parameter (DBZD). By testing the sensors across a hydrogen concentration range of 20 ppb to 3 v/v%, the optimal annealing temperature (250 °C) and operating temperature (60 °C) were identified. Under these conditions, the sensor exhibited a detection limit as low as 20 ppb with a power consumption of only 4.6 mW. At the same time, the response and recovery times of the sensor were 6 and 19 s, respectively, toward 3 v/v% hydrogen. After testing over a 100-day period, Ra fluctuated only 0.0026%, indicating that the hydrogen sensor had good long-term stability for low-concentration detection. More results also showed that the sensor has good repeatability, selectivity, and humidity resistance. With the wide measurement range (20 ppb to 3 v/v%), the sensor has the potential to meet hydrogen detection requirements in multiple scenarios.

Signal conditioning system for real-time monitoring of unbalanced mass and angular position in helicopter propeller rotor balancing

This paper outlines the design of a signal conditioning system developed to enable real-time monitoring of unbalanced mass and rotor angular position on a horizontal balancing machine. The system incorporates piezoelectric sensors with high sensitivity and a wide measurement range, allowing them to detect small variations in acceleration with great accuracy. Therefore, the proposed signal conditioning system relies on a lock-in amplifier, which can measure small signals even in the presence of considerable noise. The system achieved an error rate of 1% or less in the mass balance of a rotor at different speeds. These results revealed a consistent linear relationship between the unbalanced mass and the rotor velocity, which simplifies the interpretation and analysis of the data, allowing any variation in the signal to be directly related to changes in the unbalanced mass or rotor velocity, without any complications due to nonlinear effects.

Vacuum Filtration-Coated Silver Electrodes Coupled with Stacked Conductive Multi-Walled Carbon Nanotubes/Mulberry Paper Sensing Layers for a Highly Sensitive and Wide-Range Flexible Pressure Sensor

Flexible pressure sensors based on paper have attracted considerable attention owing to their good performance, low cost, and environmental friendliness. However, effectively expanding the detection range of paper-based sensors with high sensitivities is still a challenge. Herein, we present a paper-based resistive pressure sensor with a sandwich structure consisting of two electrodes and three sensing layers. The silver nanowires were dispersed deposited on a filter paper substrate using the vacuum filtration coating method to prepare the electrode. And the sensing layer was fabricated by coating carbon nanotubes onto a mulberry paper substrate. Waterborne polyurethane was introduced in the process of preparing the sensing layers to enhance the strength of the interface between the carbon nanotubes and the mulberry paper substrate. Therefore, the designed sensor exhibits a good sensing performance by virtue of the rational structure design and proper material selection. Specifically, the rough surfaces of the sensing layers, porous conductive network of silver nanowires on the electrodes, and the multilayer stacked structure of the sensor collaboratively increase the change in the surface contact area under a pressure load, which improves the sensitivity and extends the sensing range simultaneously. Consequently, the designed sensor exhibits a high sensitivity (up to 6.26 kPa−1), wide measurement range (1000 kPa), low detection limit (~1 Pa), and excellent stability (1000 cycles). All these advantages guarantee that the sensor has potential for applications in smart wearable devices and the Internet of Things.

Arch dam point cloud segmentation based on deep feature learning and normal vector data optimization

Separating the dam body, spillway, and other structures from the point cloud in the dam area is an important step in dam deformation monitoring. Manual segmentation is time consuming and inaccurate. This study proposes a point cloud segmentation neural network model based on normal vector optimization suitable for dam environment: (1) This model utilizes the voxel uniform sampling method of equal length cubes to solve the problem of uneven point cloud density caused by wide range and long-distance measurement during point cloud measurement in dam areas. (2) Designed block input and combined output modules in the model, achieving efficient input of large volume point cloud and eliminating the impact of interpolation points offset during seq2seq model decoding process. (3) In response to the diverse characteristics of point cloud normal vectors presented by vegetation, rock mass, and complex dam structures in the dam area, this paper proposes an adaptive radius plane fitting vector estimation method based on eigenvalue method to improve the accuracy of segmentation. The experiment on the prototype arch dam shows that the proposed normal estimation method improves the classification accuracy of PointNet + + from 96.26 to 98.27%. Compared with the other three normal estimation methods (2-jets, Hough CNN, iterative PCA), the overall accuracy is improved by 0.82%, 1.22%, and 0.22%, and the joint average intersection is improved by 0.0293, 0.0325, and 0.0104. The prototype arch dam experiment shows that our proposed method has a segmentation accuracy of 98.27%. Compared with 2-jets, Hough CNN, and iterative PCA, the overall accuracy has been improved by 0.82%, 1.22%, and 0.22%. This study provides a high-precision segmentation scheme for applications such as deformation detection of dam components based on point clouds.

Degradable Multilayer Fabric Sensor with Wide Detection Range and High Linearity.

Integration of multiple superior features into a single flexible pressure sensor would result in devices with greater versatility and utility. To apply the device to a variety of scenarios and solve the problem of accumulation of e-waste in the environment, it is highly desirable to combine degradability and wide-range linearity characteristics in a single device. Herein, we reported a degradable multilayer fabric (DMF) consisting of an ellipsoidal carbon nanotube (ECNT) and polyvinylpyrrolidone/cellulose acetate electrospun fibers (PEF). The alternative layer-by-layer stacking of the ECNT and PEF notably accelerates the sensitivity toward pressure. The optimized device demonstrated a sensitivity of 3.38 kPa-1 over a wide measurement range from 0.1 to 500 kPa, as well as great mechanical stability over 2000 cycles. A good degradation performance was confirmed by both Fourier transform infrared (FTIR) characterization and decomposition experiments in sodium hydroxide solution. The fabricated sensor is capable of precepting a variety of physiological scenarios including subtle arterial pulse, dancing training, walking postures, and accidental falls. This work throws light onto the fundamental understanding of the mechanical interfacial coupling in piezoresistive materials and provides possibilities for the design and development of on-demand wearable electronics.

“Between formulas and freestyle” – a qualitative analysis of peer tutor preparation and its impact on peer relations

BackgroundPeer tutorials are widely used in medical and health professions education. Some evidence suggests that peer tutorials can have positive effects for student peer tutors and tutees alike. To promote these positive effects, peer tutors are often prepared for their tasks. However, detailed information about this preparation is missing in the literature. The present study thus examines from the tutors’ perspective how peer tutor preparation is conducted, both in interprofessional and uniprofessional contexts, and how this preparation affects peer relations.MethodsA qualitative design was used for the study. For data gathering, three online focus group discussions were conducted with student peer tutors from uniprofessional and interprofessional settings who had a background in health professions. Data were analysed inductively via thematic analysis.ResultsA total of 19 individuals participated in three focus group discussions (n = 6/n = 6/n = 7). From the participants’ perspective, preparation measures were heterogenous. Of a wide range of different measures, some were perceived as more helpful, others as less helpful. In analysing the data, three relevant themes came up which were dereived from the peer tutors’ perspective: roles, eye level, and (self-)trust. All three themes were found to be closely related and appeared to have a direct influence on peer relations. This influence on the learning/teaching process was either positive or negative depending on the respondents’ experiences.ConclusionFrom the peer tutors’ perspective, the preparation they received affected their relationships with their peers in a variety of ways, influenced by the context and the peer tutors’ needs. This finding should be taken into account when planning and implementing future preparatory activities. In addition, further pedagogical considerations and discussions about preparatory activities for peer tutors and their potential impact on social and cognitive congruence are needed.

Perspective on the Development and Integration of Hydrogen Sensors for Fuel Cell Control

The measurement of hydrogen concentration in fuel cell systems is an important prerequisite for the development of a control strategy to enhance system performance, reduce purge losses and minimize fuel cell aging effects. In this perspective paper, the working principles of hydrogen sensors are analyzed and their requirements for hydrogen control in fuel cell systems are critically discussed. The wide measurement range, absence of oxygen, high humidity and limited space turn out to be most limiting. A perspective on the development of hydrogen sensors based on palladium as a gas-sensitive metal and based on the organic magnetic field effect in organic light-emitting devices is presented. The design of a test chamber, where the sensor response can easily be analyzed under fuel cell-like conditions is proposed. This allows the generation of practical knowledge for further sensor development. The presented sensors could be integrated into the end plate to measure the hydrogen concentration at the anode in- and outlet. Further miniaturization is necessary to integrate them into the flow field of the fuel cell to avoid fuel starvation in each single cell. Compressed sensing methods are used for more efficient data analysis. By using a dynamical sensor model, control algorithms are applied with high frequency to control the hydrogen concentration, the purge process, and the recirculation pump.

Impact of coffee-derived chlorogenic acid on cognition: a systematic review and meta-analysis.

Coffee drinking has been associated with benefits for various health outcomes, with many attributed to the most prevalent family of polyphenols within coffee, chlorogenic acids (CGA). Whilst reviews of the association between coffee and cognition exist, evidence exploring effects of coffee-specific CGA on cognition has yet to be systematically synthesised. The purpose was to systematically review the current literature investigating the relationship between CGA from coffee and cognitive performance. A further objective was to undertake a meta-analysis of relevant randomised controlled trials (RCT). Observational and intervention studies were included if they considered coffee-based CGA consumption in human participants and applied a standardised measure of cognition. Furthermore, intervention studies were required to define the CGA content and include a control group/placebo. Studies were excluded if they examined CGA alone as an extract or supplement. A search of Scopus, PubMed, Web of Science, ScienceDirect and PsycINFO resulted in including twenty-three papers, six of which were interventions. The evidence from the broader systematic review suggests that CGA from coffee may need to be consumed chronically over a sustained period to produce cognitive benefits. However, the meta-analysis of RCT showed no benefits of coffee CGA intake on cognitive function (d = 0.00, 95% CI -0.05, 0.05). Overall, this review included a limited number of studies, the sample sizes were small, and a wide range of cognitive measures have been utilised. This indicates that further, good-quality interventions and RCT are required to systematically explore the conditions under which coffee CGA may provide benefits for cognitive outcomes.

Core Potentials: The Consensus Segmentation Conjecture

Segmentations are partitions of an ordered set into non-overlapping intervals. The Consensus Segmentation or Segmentation Aggregation problem is a special case of the median problems with applications in time series analysis and computational biology. A wide range of dissimilarity measures for segmentations can be expressed in terms of potentials, a special type of set-functions. In this contribution, we shed more light on the properties of potentials, and how such properties affect the solutions of the Consensus Segmentation problem. In particular, we disprove a conjecture stated in 2021, and we provide further insights into the theoretical foundations of the problem.

A-009 Analytical Characterization of a Novel NT-proBNP Assay on a Central Laboratory Platform

Abstract Background N-terminal pro-B-type Natriuretic Peptide (NT-proBNP) or B-type Natriuretic Peptide (BNP) assay(s) are widely measured with a Class 1, Level of Evidence A recommendation in professional heart failure (HF) guidelines for diagnosis and prognosis. We present the analytical characteristics of the first NT-proBNP assay on Beckman Coulter platforms. Methods Measurements were conducted with the Access NT-proBNP assay, a one-step sandwich immunoenzymatic assay using monoclonal capture and detection antibodies, on the DxI 9000 Immunoassay Analyzer with Lithium Heparin (LiHep) plasma samples. Performance was characterized according to CLSI guidelines for: Limit of Blank (LoB), Limit of Detection (LoD), Limit of Quantitation (LoQ), linearity, imprecision (repeatability, reproducibility) and matrix comparison with LiHep, EDTA and serum. Reference intervals (RI) were evaluated in a healthy, adult U.S. population comprised of 675 subjects with 54.6% females, 79.1% White and 15.1% Black individuals. Exclusion criteria included elevated cardiac troponin, abnormal eGFR and cardiac medications. The 97.5th percentile RI upper limit was defined for age-stratified ranges of <50, 50-75, and >75 years old. Results Performance was LoB=1.1ng/L; LoD=4.8ng/L; LoQ=4.8ng/L; linearity=35,000ng/L. Repeatability ranged from 1.5%-3.5% and reproducibility from 2.3%-7.9% in seven samples ranging from 38ng/L to 23,848ng/L. Matrix measurement regression (n=68) yielded slopes of 1.00, 1.01; intercepts -0.03 to -2.63; r=0.98. Table 1 shows that NT-proBNP values increase with age and women generally have higher values than men. Conclusions The LoB, LoD and LoQ demonstrate highly sensitive low-end characteristics. Repeatability and reproducibility show excellent performance across a wide measurement range. NT-proBNP values are known to be age dependent, and the age-stratified 97.5th percentile RI upper limits were 162 ng/L for <50 years, 311 ng/L for 50-70 years, and 457 ng/L for >75 years. This novel Access NT-proBNP assay offers robust analytical performance as an aid to clinical HF management in acute settings.

Global-scale gravity wave analysis methodology for the ESA Earth Explorer 11 candidate CAIRT

Abstract. In the past, satellite climatologies of gravity waves (GWs) have initiated progress in their representation in global models. However, these could not provide the phase speed and direction distributions needed for a better understanding of the interaction between GWs and the large-scale winds directly. The ESA Earth Explorer 11 candidate CAIRT could provide such observations. CAIRT would use a limb-imaging Michelson interferometer resolving a wide spectral range, allowing temperature and trace gas mixing ratio measurements. With the proposed instrument design, a vertical resolution of 1 km, along-track sampling of 50 km, and across-track sampling of 25 km in a 400 km wide swath will be achieved. In particular, this allows for the observation of three-dimensional (3D), GW-resolving temperature fields throughout the middle atmosphere. In this work, we present the methodology for the GW analysis of CAIRT observations using a limited-volume 3D sinusoidal fit (S3D) wave analysis technique. We assess the capability of CAIRT to provide high-quality GW fields by the generation of synthetic satellite observations from high-resolution model data and comparison of the synthetic observations to the original model fields. For the assessment, wavelength spectra, phase speed spectra, horizontal distributions, and zonal means of GW momentum flux (GWMF) are considered. The atmospheric events we use to exemplify the capabilities of CAIRT are the 2006 sudden stratospheric warming (SSW) event, the quasi-biennial oscillation (QBO) in the tropics, and the mesospheric preconditioning phase of the 2019 SSW event. Our findings indicate that CAIRT would provide highly reliable observations not only of global-scale GW distributions and drag patterns but also of specific wave events and their associated wave parameters. Even under worse-than-expected noise levels of the instrument, the resulting GW measurements are highly consistent with the original model data. Furthermore, we demonstrate that the estimated GW parameters can be used for ray tracing, which physically extends the horizontal coverage of the observations beyond the orbit tracks.

Association of H-reflex parameters and peroneal nerve conduction velocity with dynamic balance and agility in university athletes: a cross-sectional study

Abstract Athletic performance parameters encompass a wide range of physical, physiological, and biomechanical measures that are crucial for evaluating and optimising athletes’ capabilities. There are various intrinsic factors that can contribute to athletic skills, which subsequently impact overall performance. Thus, there is a need to explore significant intrinsic factors associated with athletic parameters, that can provide insights into the physiological mechanisms underlying performance. In this study, we examined the potential relationship of two such intrinsic factors, namely the H-reflex and the peroneal nerve conduction velocity, with athletic skills like dynamic balance and agility. Forty-five university-level athletes of all genders playing for different teams of Jamia Millia Islamia University, New Delhi, India were selected. All athletes underwent tibial H-reflex, peroneal NCV, mSEBT (for dynamic balance), and agility T-test evaluations. The Pearson correlation coefficient was calculated to evaluate the association of nerve function parameters (H-reflex and NCV) with athletic performance parameters (dynamic balance and agility). Results showed that H-reflex amplitude showed a significant negative correlation with both dynamic balance scores (Dominant Leg [DL]: r = −0.321 and ; Non-dominant leg [NDL]: r = −0.397 and ) and T-test scores (DL: r = −0.342; NDL: r = −0.321, ), respectively. The peroneal NCV was significantly positively correlated with dynamic balance (DL: r = 0.438 and ; NDL: r = 0.418 and ) and agility scores (DL: r = 0.639 and ; NDL: r = 0.641 and ) in athletes. In conclusion, significant associations were found between H-reflex and Peroneal nerve conduction velocity and key athletic performance parameters like dynamic balance and agility among university athletes. This implies that neural function is closely linked with athletic skills and performance. Registered in Clinical Trials Registry-India (CTRI) under registration number: REF/2023/11/075394.

Carers in post-stroke aphasia: a scoping review of interventions and outcomes beyond communication partner training

Purpose Carers of people with aphasia face unique challenges. Research has demonstrated that these carers have a higher burden of care and more negative stroke-related outcomes in comparison to carers of stroke survivors without aphasia. The aim of this scoping review was to map the range of interventions for carers other than communication partner training and to examine their outcomes. Materials and methods We conducted a scoping review on this topic. Results Twenty studies were included. Most studies were case series with four randomised control trials. Both quantitative and qualitative approaches were used. Most studies occurred during the long-term phase of care. Two interventions had only carers as participants. Interventions were comprised of different combinations of intervention components including psychoeducation, skill-building, and support. There was high variability on who led the interventions, the format, and the dose/schedule. Twenty-eight different outcome measures for carers and dyads were used across various domains with overall positive outcomes post-intervention. Conclusions This review uncovered a wide range of formats, dosages, and outcome measures in interventions for carers. Encouragingly, the majority of these interventions included psychoeducation, skill-building, and support components. While most studies were case series, there are promising interventions that have the potential to enhance carer wellbeing.

Prediction of new-onset atrial fibrillation in patients with non-small cell lung cancer treated with curative-intent conventional radiotherapy

BackgroundAtrial fibrillation (AF) is an important side effect of thoracic Radiotherapy (RT), which may impair quality of life and survival. This study aimed to develop a prediction model for new-onset AF in patients with Non-Small Cell Lung Cancer (NSCLC) receiving RT alone or as a part of their multi-modal treatment. Patients and MethodsPatients with stage I-IV NSCLC treated with curative-intent conventional photon RT were included. The baseline electrocardiogram (ECG) was compared with follow-up ECGs to identify the occurrence of new-onset AF. A wide range of potential clinical predictors and dose-volume measures on the whole heart and six automatically contoured cardiac substructures, including chambers and conduction nodes, were considered for statistical modeling. Internal validation with optimism-correction was performed. A nomogram was made. Results374 patients (mean age 69 ± 10 years, 57 % male) were included. At baseline, 9.1 % of patients had AF, and 42 (11.2 %) patients developed new-onset AF. The following parameters were predictive: older age (OR=1.04, 95 % CI: 1.013–1.068), being overweight or obese (OR=1.791, 95 % CI: 1.139–2.816), alcohol use (OR=4.052, 95 % CI: 2.445–6.715), history of cardiac procedures (OR=2.329, 95 % CI: 1.287–4.215), tumor located in the upper lobe (OR=2.571, 95 % CI: 1.518–4.355), higher forced expiratory volume in 1 s (OR=0.989, 95 % CI: 0.979–0.999), higher creatinine (OR=1.008, 95 % CI: 1.002–1.014), concurrent chemotherapy (OR=3.266, 95 % CI: 1.757 to 6.07) and left atrium Dmax (OR=1.022, 95 % CI: 1.012–1.032). The model showed good discrimination (area under the curve = 0.80, 95 % CI: 0.76–0.84), calibration and positive net benefits. ConclusionThis prediction model employs readily available predictors to identify patients at high risk of new-onset AF who could potentially benefit from active screening and timely management of post-RT AF.

Правове регулювання запобігання корупційним проявам в діяльності державної прикордонної служби в Україні в умовах воєнного стану

The article analyzes the legal regulation on the prevention of corruption in the activities of the State Border Service of Ukraine (SBSU) during martial law. Corruption poses a significant risk to national security, the efficiency of public resource management, economic development, and the stability of government. The legal definition of corruption refers to the use of official powers to obtain an unlawful benefit. In the context of martial law, the DPSU faced increased threats of corruption, in particular when controlling the state border. The article analyzes the main categories of anti-corruption legislation, including the prevention, prevention, prevention and counteraction of corruption, and also examines measures that can effectively reduce corruption risks in public administration. The main initiatives for the prevention of corruption cover a wide range of legal, organizational and educational measures aimed at eliminating the causes and conditions that can contribute to the commission of illegal actions.Effective management and control of state borders becomes especially important during martial law, when national security depends on the reliability of anti-corruption measures. In this context, the improvement of the legislative framework regulating the activities of the State Border Service of Ukraine, in particular regarding granting it the status of administrator of the Unified State Register of conscripts, conscripts and reservists, is important for strengthening control and reducing corruption risks at the border. Such changes will not only ensure more effective monitoring and compliance of border crossers with military and legal obligations, but will also help prevent the illegal movement of people across the border. These measures play a key role in ensuring the country’s internal stability and defense capability, especially in the face of military threats. Updating the legislation will also strengthen the legality of border service actions and increase their transparency, which is necessary to maintain citizens’ trust in state institutions.

Universally consistent K-sample tests via dependence measures

The K-sample testing problem involves determining whether K groups of data points are each drawn from the same distribution. Analysis of variance is arguably the most classical method to test mean differences, along with several recent methods to test distributional differences. In this paper, we demonstrate the existence of a transformation that allows K-sample testing to be carried out using any dependence measure. Consequently, universally consistent K-sample testing can be achieved using a universally consistent dependence measure, such as distance correlation and the Hilbert–Schmidt independence criterion. This enables a wide range of dependence measures to be easily applied to K-sample testing.

Phase fraction measurement of gas-liquid flow based on cyclonic capacitive sensor (CCS) and inverse drift flux method

Abstract As the demand for clean energy sources like natural gas increases, the need for methods to measure the phase fraction of gas-liquid two-phase flows, which have complex and variable flow patterns, becomes more pronounced. This study introduces a phase fraction measurement method based on a cyclonic capacitive sensor. An effective phase fraction prediction model for the gas-liquid flow measurement section is established based on the capacitive signals. Using the drift flux principle, the dimensionless drift velocity of the spiral annular flow is analyzed, and a volume gas fraction (GVF) prediction model based on the ‘inverse drift flux method’ is established. Experimental results show that this method is suitable for a wide range of phase fraction measurements and is highly accurate. When the liquid volume fraction (LVF) is less than 10%, the average relative error of the predicted GVF is 0.3%; for the LVF from 10% to 30%, the average relative error is 1.4%.

Highly sensitive push-pull differential pressure sensor with multi-parameter measurement capabilities

A multi-parameter sensor comprising of a Fabry–Perot (FP) pair and a fiber-optic FP microcavity was proposed for simultaneous measurement of differential pressure (DP), static pressure (SP) and temperature. The push-pull FP pair is used to measure the differential pressure, and wide measurement range can be achieved by adjusting the dimensions of the diaphragm. The self-enclosed fiber-optic microcavity is utilized to measure the static pressure. For multi-parameter measurement, a matrix equation is proposed to solve the differential pressure, static pressure and temperature by fully considering the relationship of the FP cavity lengths and measurands. The performance of multi-parameter sensing is verified experimentally. The sensitivities of differential pressure, static pressure and temperature are 294.4822 nm/KPa, 353.08 nm/MPa and 42.4056 nm/°C, respectively, in variation of cavity lengths. The sensing characteristics show good linearity. Such a sensor could find important applications in the fields of process industry and oil industry, etc.